In the recent years, large scale information transfer by remote computing and the development
of massive storage and retrieval systems have witnessed a tremendous growth. To cope up with the
growth in the size of databases, additional storage devices need to be installed and the modems and
multiplexers have to be continuously upgraded in order to permit large amounts of data transfer between
computers and remote terminals. This leads to an increase in the cost as well as equipment. One solution
to these problems is “COMPRESSION” where the database and the transmission sequence can be
encoded efficiently. In this we investigated for optimum wavelet, optimum level, and optimum scaling
factor.
1) The document discusses audio compression using Daubechie wavelets. It involves using optimal wavelet selection and quantizing wavelet coefficients along with A-law and U-law companding methods.
2) The key steps of wavelet-based audio compression are thresholding and quantizing wavelet coefficients, then encoding the data to remove redundancy and reduce the number of coefficients.
3) A psychoacoustic model is incorporated to determine inaudible quantization noise levels based on auditory masking principles. The masking thresholds are converted to constraints in the wavelet domain to guide coefficient quantization and selection of an optimal wavelet basis.
IRJET- Reconstruction of Sparse Signals(Speech) Using Compressive SensingIRJET Journal
This document discusses reconstructing sparse speech signals using compressive sensing. Compressive sensing allows reconstructing signals from fewer samples than the Nyquist rate by exploiting signal sparsity. The paper proposes using the basis pursuit algorithm to reconstruct speech signals sampled below the Nyquist rate. Basis pursuit formulates reconstruction as an l1-norm optimization problem to find the sparsest solution matching the samples. The algorithm is implemented in MATLAB and results show basis pursuit can accurately reconstruct speech signals from undersampled measurements without noise.
This document discusses discrete-time signal processing and audio signal processing. It covers topics like discrete-time signals, the z-transform, discrete Fourier transform (DFT) and fast Fourier transform (FFT). The key points are:
- Audio signals are typically sampled at 44.1 kHz and quantized to 16 bits per sample.
- The z-transform and discrete Fourier transform (DTFT) are used to analyze discrete-time signals in the transform domain, similar to the Laplace transform and continuous-time Fourier transform for analog signals.
- The discrete Fourier transform (DFT) provides a computational tool to calculate Fourier transforms by sampling the frequency domain at discrete points, resulting in periodicity in the time and
Dwpt Based FFT and Its Application to SNR Estimation in OFDM SystemsCSCJournals
This document discusses a wavelet packet transform based fast Fourier transform (DWPT-FFT) and its application to signal-to-noise ratio (SNR) estimation in orthogonal frequency division multiplexing (OFDM) systems. The DWPT-FFT has the same computational complexity as the conventional FFT but provides finer frequency resolution. An SNR estimation technique is proposed that performs estimation inside the DWPT-FFT block, unlike previous methods that estimate SNR after FFT. The technique divides the OFDM band into sub-bands using wavelet packets and estimates noise power in each sub-band based on the autocorrelation of the transmitted preamble. The proposed estimator is compared to Reddy's estimator through simulations and shows improved performance in colored noise scenarios.
Data Compression using Multiple Transformation Techniques for Audio Applicati...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Design of matched filter for radar applicationselelijjournal
The aim of this paper is to present the details of signal processing techniques in Military RADARS . These
techniques are strongly based on mathematics and specially on stochastic processes. Detecting a target in
a noisy environment is a many folds sequential process. The signal processing chain only provides to the
overall system boolean indicators stating the presence (or not) of targets inside the coverage area. It is
part of the strategical operation of the radar. This paper mainly focuses on Design of Matched filter and
generation of chirp Signal.
Reducting Power Dissipation in Fir Filter: an AnalysisCSCJournals
This document summarizes and analyzes three existing techniques for reducing power consumption in FIR filters: signed power-of-two representation, steepest descent optimization, and coefficient segmentation. It finds that steepest descent can reduce hamming distance between coefficients by up to 26%, while coefficient segmentation can achieve up to 47% reduction. However, both techniques degrade filter performance parameters slightly. Signed power-of-two representation provides the most power reduction of 63% but introduces overhead from additional adders and shifters. The document evaluates these techniques on four low-pass FIR filters and concludes there is a tradeoff between hamming distance reduction and degradation of filter specifications.
Real-time DSP Implementation of Audio Crosstalk Cancellation using Mixed Unif...CSCJournals
For high fidelity sound reproduction, it is necessary to use long filter coefficients in audio crosstalk cancellation. To implement these long filters on real-time DSP processors, conventional overlap save technique suffers from more computational power as well as processing delay. To overcome these technical problems, mixed uniform partitioned convolution technique is proposed. This method is derived by combining uniform partitioned convolution with mixed filtering technique. With the proposed method, it is possible to perform audio crosstalk cancellation even at the order of ten thousand filter taps with less computations and short processing delay. The proposed technique was implemented on 32-bit floating point DSP processor and design was provided with efficient memory management to achieve optimization in computational complexity. The computational comparison of this method with conventional methods shows that the proposed technique is very efficient for long filters
1) The document discusses audio compression using Daubechie wavelets. It involves using optimal wavelet selection and quantizing wavelet coefficients along with A-law and U-law companding methods.
2) The key steps of wavelet-based audio compression are thresholding and quantizing wavelet coefficients, then encoding the data to remove redundancy and reduce the number of coefficients.
3) A psychoacoustic model is incorporated to determine inaudible quantization noise levels based on auditory masking principles. The masking thresholds are converted to constraints in the wavelet domain to guide coefficient quantization and selection of an optimal wavelet basis.
IRJET- Reconstruction of Sparse Signals(Speech) Using Compressive SensingIRJET Journal
This document discusses reconstructing sparse speech signals using compressive sensing. Compressive sensing allows reconstructing signals from fewer samples than the Nyquist rate by exploiting signal sparsity. The paper proposes using the basis pursuit algorithm to reconstruct speech signals sampled below the Nyquist rate. Basis pursuit formulates reconstruction as an l1-norm optimization problem to find the sparsest solution matching the samples. The algorithm is implemented in MATLAB and results show basis pursuit can accurately reconstruct speech signals from undersampled measurements without noise.
This document discusses discrete-time signal processing and audio signal processing. It covers topics like discrete-time signals, the z-transform, discrete Fourier transform (DFT) and fast Fourier transform (FFT). The key points are:
- Audio signals are typically sampled at 44.1 kHz and quantized to 16 bits per sample.
- The z-transform and discrete Fourier transform (DTFT) are used to analyze discrete-time signals in the transform domain, similar to the Laplace transform and continuous-time Fourier transform for analog signals.
- The discrete Fourier transform (DFT) provides a computational tool to calculate Fourier transforms by sampling the frequency domain at discrete points, resulting in periodicity in the time and
Dwpt Based FFT and Its Application to SNR Estimation in OFDM SystemsCSCJournals
This document discusses a wavelet packet transform based fast Fourier transform (DWPT-FFT) and its application to signal-to-noise ratio (SNR) estimation in orthogonal frequency division multiplexing (OFDM) systems. The DWPT-FFT has the same computational complexity as the conventional FFT but provides finer frequency resolution. An SNR estimation technique is proposed that performs estimation inside the DWPT-FFT block, unlike previous methods that estimate SNR after FFT. The technique divides the OFDM band into sub-bands using wavelet packets and estimates noise power in each sub-band based on the autocorrelation of the transmitted preamble. The proposed estimator is compared to Reddy's estimator through simulations and shows improved performance in colored noise scenarios.
Data Compression using Multiple Transformation Techniques for Audio Applicati...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Design of matched filter for radar applicationselelijjournal
The aim of this paper is to present the details of signal processing techniques in Military RADARS . These
techniques are strongly based on mathematics and specially on stochastic processes. Detecting a target in
a noisy environment is a many folds sequential process. The signal processing chain only provides to the
overall system boolean indicators stating the presence (or not) of targets inside the coverage area. It is
part of the strategical operation of the radar. This paper mainly focuses on Design of Matched filter and
generation of chirp Signal.
Reducting Power Dissipation in Fir Filter: an AnalysisCSCJournals
This document summarizes and analyzes three existing techniques for reducing power consumption in FIR filters: signed power-of-two representation, steepest descent optimization, and coefficient segmentation. It finds that steepest descent can reduce hamming distance between coefficients by up to 26%, while coefficient segmentation can achieve up to 47% reduction. However, both techniques degrade filter performance parameters slightly. Signed power-of-two representation provides the most power reduction of 63% but introduces overhead from additional adders and shifters. The document evaluates these techniques on four low-pass FIR filters and concludes there is a tradeoff between hamming distance reduction and degradation of filter specifications.
Real-time DSP Implementation of Audio Crosstalk Cancellation using Mixed Unif...CSCJournals
For high fidelity sound reproduction, it is necessary to use long filter coefficients in audio crosstalk cancellation. To implement these long filters on real-time DSP processors, conventional overlap save technique suffers from more computational power as well as processing delay. To overcome these technical problems, mixed uniform partitioned convolution technique is proposed. This method is derived by combining uniform partitioned convolution with mixed filtering technique. With the proposed method, it is possible to perform audio crosstalk cancellation even at the order of ten thousand filter taps with less computations and short processing delay. The proposed technique was implemented on 32-bit floating point DSP processor and design was provided with efficient memory management to achieve optimization in computational complexity. The computational comparison of this method with conventional methods shows that the proposed technique is very efficient for long filters
This document summarizes a research paper that presents a speech enhancement method using stationary wavelet transform. The method first classifies speech into voiced, unvoiced, and silence regions based on short-time energy. It then applies different thresholding techniques to the wavelet coefficients of each region - modified hard thresholding for voiced speech, semi-soft thresholding for unvoiced speech, and setting coefficients to zero for silence. Experimental results using speech from the TIMIT database corrupted with white Gaussian noise at various SNR levels show improved performance over other popular denoising methods.
IRJET- Wavelet Transform based SteganographyIRJET Journal
This document proposes an image steganography technique to hide audio signals in images using wavelet transforms. It discusses how discrete wavelet transform (DWT) can be used to decompose images and audio into different frequency subbands. The technique encrypts an audio file (MP3 or WAV) and hides it in the wavelet coefficients of an image. When extracted, the secret audio signal is decrypted. The quality of the stego image and extracted audio is measured using metrics like PSNR, SSIM, SNR, and SPCC. The results show good quality for the steganography technique and that it can withstand various attacks.
A Combined Voice Activity Detector Based On Singular Value Decomposition and ...CSCJournals
voice activity detector (VAD) is used to separate the speech data included parts from silence parts of the signal. In this paper a new VAD algorithm is represented on the basis of singular value decomposition. There are two sections to perform the feature vector extraction. In first section voiced frames are separated from unvoiced and silence frames. In second section unvoiced frames are silence frames. To perform the above sections, first, windowing the noisy signal then Hankel’s matrix is formed for each frame. The basis of statistical feature extraction of purposed system is slope of singular value curve related to each frame by using linear regression. It is shown that the slope of singular values curve per different SNRs in voiced frames is more than the other types and this property can be to achieve the goal the first part can be used. High similarity between feature vector of unvoiced and silence frame caused to approach for separation of the two categories above cannot be used. So in the second part, the frequency characteristics for identification of unvoiced frames from silent frames have been used. Simulation results show that high speed and accuracy are the advantages of the proposed system.
Analysis of Microstrip Finger on Bandwidth of Interdigital Band Pass Filter u...IJREST
This document discusses using artificial neural networks to estimate the bandwidth of an interdigital band pass filter based on variations in the finger length. An ANN model was developed using data from electromagnetic simulations of filters with finger lengths ranging from 34mm to 24mm. Both multi-layer perceptron and radial basis function networks were tested, with the RBF network providing more accurate results with a mean squared error of 1.13173e-005. The proposed ANN approach allows estimating the filter bandwidth without complex calculations and provides a fast design method for interdigital band pass filters.
Audio compression has become one of the basic technologies of the multimedia age. The change in the telecommunication infrastructure, in recent years, from circuit switched to packet switched systems has also reflected on the way that speech and audio signals are carried in present systems. In many applications, such as the design of multimedia workstations and high quality audio transmission and storage, the goal is to achieve transparent coding of audio and speech signals at the lowest possible data rates. In other words, bandwidth cost money, therefore, the transmission and storage of information becomes costly. However, if we can use less data, both transmission and storage become cheaper. Further reduction in bit rate is an attractive proposition in applications like remote broadcast lines, studio links, satellite transmission of high quality audio and voice over internet.
IRJET- Efficient Shift add Implementation of Fir Filter using Variable Pa...IRJET Journal
This document discusses efficient implementations of shift-add operations in finite impulse response (FIR) filters using variable partition hybrid form structures. FIR filters are widely used in digital signal processing and their performance is dominated by multiplication operations. The proposed method aims to reduce power consumption and complexity by implementing multiplications using optimized shift-add networks instead of multipliers. It explores variable size partitioning approaches and prefix adders to reduce gate count, dynamic power, and improve filter performance.
IRJET- Pitch Detection Algorithms in Time DomainIRJET Journal
This document discusses pitch detection algorithms in the time domain. It describes two common time domain pitch detection methods: the autocorrelation method and average magnitude difference function (AMDF) method. The autocorrelation method detects the periodicity of a speech signal by finding the highest value of the autocorrelation function. The AMDF method calculates the average magnitude of differences between the original and delayed speech signal at different lags, and identifies the pitch period as the lag with the minimum AMDF value. The document also provides implementation results of these two methods on speech samples, demonstrating their ability to estimate pitch periods in the time domain.
Performance Analysis of Acoustic Echo Cancellation TechniquesIJERA Editor
Mainly, the adaptive filters are implemented in time domain which works efficiently in most of the applications. But in many applications the impulse response becomes too large, which increases the complexity of the adaptive filter beyond a level where it can no longer be implemented efficiently in time domain. An example of where this can happen would be acoustic echo cancellation (AEC) applications. So, there exists an alternative solution i.e. to implement the filters in frequency domain. AEC has so many applications in wide variety of problems in industrial operations, manufacturing and consumer products. Here in this paper, a comparative analysis of different acoustic echo cancellation techniques i.e. Frequency domain adaptive filter (FDAF), Least mean square (LMS), Normalized least mean square (NLMS) &Sign error (SE) is presented. The results are compared with different values of step sizes and the performance of these techniques is measured in terms of Error rate loss enhancement (ERLE), Mean square error (MSE)& Peak signal to noise ratio (PSNR).
A New Method for Pitch Tracking and Voicing Decision Based on Spectral Multi-...CSCJournals
This paper proposes a new voicing detection and pitch estimation method that is particularly robust for noisy speech. This method is based on the spectral analysis of the speech multi-scale product. The multi-scale product (MP) consists of making the product of wavelet transform coefficients. The wavelet used is the quadratic spline function. We argue that the spectral of Multi-scale Product Analysis is capable of revealing an estimate of a pitch-harmonic more accurately even in a heavy noisy scenario. We evaluate our approach on the Keele database. The experimental results show the robustness of our method for noisy speech, and the good performance for clean speech in comparison with state-of-the-art algorithms.
This document discusses performance of matching algorithms for signal approximation. It begins by introducing matching pursuit algorithms like Orthogonal Matching Pursuit (OMP) and Stagewise Orthogonal Matching Pursuit (StOMP) which are greedy algorithms that approximate sparse signals. It then describes the Non-Negative Least Squares algorithm which solves non-negative least squares problems. Finally, it discusses Extranious Equivalent Detection (EED), a modification of OED that incorporates non-negativity of representations by using a non-negative optimization technique instead of orthogonal projection.
Comparative evaluation of bit error rate for different ofdm subcarriers in ra...ijmnct
In the present situation, the expectation about the quality of signals in wireless communication is as high as possible. This quality issue is dependent upon the different communication parameters. One of the most important issues is to reduce the bit error rate (BER) to enhance the performance of the system. This paper provides a comparative analysis on the basis of this bit error rate. I have compared the BER for different number of subcarriers in OFDM system for BPSK modulation scheme. I have taken 6 varieties of data subcarriers to analyze this comparison. Here my target is to reach at the lowest level of BER for BPSK modulation. That is achieved at 2048 number of subcarriers.
OFDM PAPR Reduction Using Hybrid Partial Transmit Sequences Based On Cuckoo S...IJERA Editor
The past decade has seen many radical changes and achievements in the field of wireless communication. Applications of wireless communication have grown swiftly in the recent past. This rigorous growth leads to more throughput over wireless channels along with increased reliability. But still the bandwidth demands are endless and increasing day by day. Today we need to constantly work towards achieving reliable wireless communication with high spectral efficiency, low complexity and good error performance results. Orthogonal frequency division multiplexing (OFDM) technique is a promising technique in this regard as it offers high data rate and reliable communications over various fading channels. But the main drawback of OFDM is the high peak to average power ratio (PAPR). In this paper we present the technique to reduce the PAPR using Cuckoo Search Algorithm in multicarrier modulation system. Simulation results show that the proposed scheme considerably outperforms the conventional system.
Compressive Sensing in Speech from LPC using Gradient Projection for Sparse R...IJERA Editor
This paper presents compressive sensing technique used for speech reconstruction using linear predictive coding because the
speech is more sparse in LPC. DCT of a speech is taken and the DCT points of sparse speech are thrown away arbitrarily.
This is achieved by making some point in DCT domain to be zero by multiplying with mask functions. From the incomplete
points in DCT domain, the original speech is reconstructed using compressive sensing and the tool used is Gradient
Projection for Sparse Reconstruction. The performance of the result is compared with direct IDCT subjectively. The
experiment is done and it is observed that the performance is better for compressive sensing than the DCT.
Performance of Matching Algorithmsfor Signal Approximationiosrjce
The document summarizes and compares several algorithms for signal approximation and sparse signal recovery, including Equivalent Detection (ED), Non-negative Equivalent Detection, Orthogonal Matching Pursuit (OMP), and Stagewise Orthogonal Matching Pursuit (StOMP). It discusses how each algorithm works, including iteratively selecting atoms from a dictionary to build up a sparse representation of the signal. OMP selects one atom per iteration while StOMP selects all atoms above a threshold. The document also discusses computational complexities of the different algorithms.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
This document summarizes a research paper on the effect of in-band crosstalk for datapath routing in WDM/DWDM networks. It discusses how in-band crosstalk, which occurs when a desired signal and unwanted signals with the same wavelength arrive at a receiver, can degrade signal quality and increase bit error rates. The paper presents a mathematical model to calculate bit error rates and power penalties at the receiver due to component crosstalk from neighboring inputs. Simulation results show that bit error rates increase with higher numbers of interfering channels and crosstalk levels. The paper concludes that receiver noise should be minimized to improve transmission performance through crosstalk reduction.
Wavelet packets provide an adaptive decomposition that overcomes limitations of the discrete wavelet transform (DWT). In wavelet packets, signal decomposition using high-pass and low-pass filters is applied recursively to both low-pass and high-pass outputs, allowing more flexible time-frequency analysis. This results in a redundant dictionary with increased flexibility but also higher computational costs. Pruning algorithms are used to select an optimal subset of bases for a given application based on cost functions related to properties like sparsity, entropy, or energy concentration.
This document discusses using deep neural networks for speech enhancement by finding a mapping between noisy and clean speech signals. It aims to handle a wide range of noises by using a large training dataset with many noise/speech combinations. Techniques like global variance equalization and dropout are used to improve generalization. Experimental results show improvements over MMSE techniques, with the ability to suppress nonstationary noise and avoid musical artifacts. The introduction provides background on speech enhancement, recognition using HMMs and other models, and the role of deep learning advances.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Interstellar Communication Theories and its PossibilitiesIJMER
This paper reviews and discusses the research dimensions in four dimensional time travel and
time dependencies of future and past on the basis of present. The paper investigates the theories that
support time travel in any manner and explore possibilities based on them for interstellar communication
Implementation of Wide Band Frequency Synthesizer Base on DFS (Digital Frequ...IJMER
Wide Band Frequency Synthesizer has become essential components in wireless communication
systems. They are used as frequency synthesizers with precise and convenient digital control in both traditional
electronics, such as televisions and AM/FM radios, and modern consumer products among which cellular
mobile phone is a striking example.
IC fabrication technology advances have made monolithic integration possible. More and more
electronic devices can be put on the same chip to reduce the number of external components and then the costs.
Therefore, on a single chip we can accomplish many functions for which we might need to make several chips
work together a few years ago. A monolithic wide-band PLL is of great interests to wireless communication
applications due to both its low cost and convenience to switch between different communication standards.
The focus of this work is to implement a wide-band Frequency Synthesizer using as few as possible building
blocks and also as simple as possible structure.
This document summarizes a research paper that presents a speech enhancement method using stationary wavelet transform. The method first classifies speech into voiced, unvoiced, and silence regions based on short-time energy. It then applies different thresholding techniques to the wavelet coefficients of each region - modified hard thresholding for voiced speech, semi-soft thresholding for unvoiced speech, and setting coefficients to zero for silence. Experimental results using speech from the TIMIT database corrupted with white Gaussian noise at various SNR levels show improved performance over other popular denoising methods.
IRJET- Wavelet Transform based SteganographyIRJET Journal
This document proposes an image steganography technique to hide audio signals in images using wavelet transforms. It discusses how discrete wavelet transform (DWT) can be used to decompose images and audio into different frequency subbands. The technique encrypts an audio file (MP3 or WAV) and hides it in the wavelet coefficients of an image. When extracted, the secret audio signal is decrypted. The quality of the stego image and extracted audio is measured using metrics like PSNR, SSIM, SNR, and SPCC. The results show good quality for the steganography technique and that it can withstand various attacks.
A Combined Voice Activity Detector Based On Singular Value Decomposition and ...CSCJournals
voice activity detector (VAD) is used to separate the speech data included parts from silence parts of the signal. In this paper a new VAD algorithm is represented on the basis of singular value decomposition. There are two sections to perform the feature vector extraction. In first section voiced frames are separated from unvoiced and silence frames. In second section unvoiced frames are silence frames. To perform the above sections, first, windowing the noisy signal then Hankel’s matrix is formed for each frame. The basis of statistical feature extraction of purposed system is slope of singular value curve related to each frame by using linear regression. It is shown that the slope of singular values curve per different SNRs in voiced frames is more than the other types and this property can be to achieve the goal the first part can be used. High similarity between feature vector of unvoiced and silence frame caused to approach for separation of the two categories above cannot be used. So in the second part, the frequency characteristics for identification of unvoiced frames from silent frames have been used. Simulation results show that high speed and accuracy are the advantages of the proposed system.
Analysis of Microstrip Finger on Bandwidth of Interdigital Band Pass Filter u...IJREST
This document discusses using artificial neural networks to estimate the bandwidth of an interdigital band pass filter based on variations in the finger length. An ANN model was developed using data from electromagnetic simulations of filters with finger lengths ranging from 34mm to 24mm. Both multi-layer perceptron and radial basis function networks were tested, with the RBF network providing more accurate results with a mean squared error of 1.13173e-005. The proposed ANN approach allows estimating the filter bandwidth without complex calculations and provides a fast design method for interdigital band pass filters.
Audio compression has become one of the basic technologies of the multimedia age. The change in the telecommunication infrastructure, in recent years, from circuit switched to packet switched systems has also reflected on the way that speech and audio signals are carried in present systems. In many applications, such as the design of multimedia workstations and high quality audio transmission and storage, the goal is to achieve transparent coding of audio and speech signals at the lowest possible data rates. In other words, bandwidth cost money, therefore, the transmission and storage of information becomes costly. However, if we can use less data, both transmission and storage become cheaper. Further reduction in bit rate is an attractive proposition in applications like remote broadcast lines, studio links, satellite transmission of high quality audio and voice over internet.
IRJET- Efficient Shift add Implementation of Fir Filter using Variable Pa...IRJET Journal
This document discusses efficient implementations of shift-add operations in finite impulse response (FIR) filters using variable partition hybrid form structures. FIR filters are widely used in digital signal processing and their performance is dominated by multiplication operations. The proposed method aims to reduce power consumption and complexity by implementing multiplications using optimized shift-add networks instead of multipliers. It explores variable size partitioning approaches and prefix adders to reduce gate count, dynamic power, and improve filter performance.
IRJET- Pitch Detection Algorithms in Time DomainIRJET Journal
This document discusses pitch detection algorithms in the time domain. It describes two common time domain pitch detection methods: the autocorrelation method and average magnitude difference function (AMDF) method. The autocorrelation method detects the periodicity of a speech signal by finding the highest value of the autocorrelation function. The AMDF method calculates the average magnitude of differences between the original and delayed speech signal at different lags, and identifies the pitch period as the lag with the minimum AMDF value. The document also provides implementation results of these two methods on speech samples, demonstrating their ability to estimate pitch periods in the time domain.
Performance Analysis of Acoustic Echo Cancellation TechniquesIJERA Editor
Mainly, the adaptive filters are implemented in time domain which works efficiently in most of the applications. But in many applications the impulse response becomes too large, which increases the complexity of the adaptive filter beyond a level where it can no longer be implemented efficiently in time domain. An example of where this can happen would be acoustic echo cancellation (AEC) applications. So, there exists an alternative solution i.e. to implement the filters in frequency domain. AEC has so many applications in wide variety of problems in industrial operations, manufacturing and consumer products. Here in this paper, a comparative analysis of different acoustic echo cancellation techniques i.e. Frequency domain adaptive filter (FDAF), Least mean square (LMS), Normalized least mean square (NLMS) &Sign error (SE) is presented. The results are compared with different values of step sizes and the performance of these techniques is measured in terms of Error rate loss enhancement (ERLE), Mean square error (MSE)& Peak signal to noise ratio (PSNR).
A New Method for Pitch Tracking and Voicing Decision Based on Spectral Multi-...CSCJournals
This paper proposes a new voicing detection and pitch estimation method that is particularly robust for noisy speech. This method is based on the spectral analysis of the speech multi-scale product. The multi-scale product (MP) consists of making the product of wavelet transform coefficients. The wavelet used is the quadratic spline function. We argue that the spectral of Multi-scale Product Analysis is capable of revealing an estimate of a pitch-harmonic more accurately even in a heavy noisy scenario. We evaluate our approach on the Keele database. The experimental results show the robustness of our method for noisy speech, and the good performance for clean speech in comparison with state-of-the-art algorithms.
This document discusses performance of matching algorithms for signal approximation. It begins by introducing matching pursuit algorithms like Orthogonal Matching Pursuit (OMP) and Stagewise Orthogonal Matching Pursuit (StOMP) which are greedy algorithms that approximate sparse signals. It then describes the Non-Negative Least Squares algorithm which solves non-negative least squares problems. Finally, it discusses Extranious Equivalent Detection (EED), a modification of OED that incorporates non-negativity of representations by using a non-negative optimization technique instead of orthogonal projection.
Comparative evaluation of bit error rate for different ofdm subcarriers in ra...ijmnct
In the present situation, the expectation about the quality of signals in wireless communication is as high as possible. This quality issue is dependent upon the different communication parameters. One of the most important issues is to reduce the bit error rate (BER) to enhance the performance of the system. This paper provides a comparative analysis on the basis of this bit error rate. I have compared the BER for different number of subcarriers in OFDM system for BPSK modulation scheme. I have taken 6 varieties of data subcarriers to analyze this comparison. Here my target is to reach at the lowest level of BER for BPSK modulation. That is achieved at 2048 number of subcarriers.
OFDM PAPR Reduction Using Hybrid Partial Transmit Sequences Based On Cuckoo S...IJERA Editor
The past decade has seen many radical changes and achievements in the field of wireless communication. Applications of wireless communication have grown swiftly in the recent past. This rigorous growth leads to more throughput over wireless channels along with increased reliability. But still the bandwidth demands are endless and increasing day by day. Today we need to constantly work towards achieving reliable wireless communication with high spectral efficiency, low complexity and good error performance results. Orthogonal frequency division multiplexing (OFDM) technique is a promising technique in this regard as it offers high data rate and reliable communications over various fading channels. But the main drawback of OFDM is the high peak to average power ratio (PAPR). In this paper we present the technique to reduce the PAPR using Cuckoo Search Algorithm in multicarrier modulation system. Simulation results show that the proposed scheme considerably outperforms the conventional system.
Compressive Sensing in Speech from LPC using Gradient Projection for Sparse R...IJERA Editor
This paper presents compressive sensing technique used for speech reconstruction using linear predictive coding because the
speech is more sparse in LPC. DCT of a speech is taken and the DCT points of sparse speech are thrown away arbitrarily.
This is achieved by making some point in DCT domain to be zero by multiplying with mask functions. From the incomplete
points in DCT domain, the original speech is reconstructed using compressive sensing and the tool used is Gradient
Projection for Sparse Reconstruction. The performance of the result is compared with direct IDCT subjectively. The
experiment is done and it is observed that the performance is better for compressive sensing than the DCT.
Performance of Matching Algorithmsfor Signal Approximationiosrjce
The document summarizes and compares several algorithms for signal approximation and sparse signal recovery, including Equivalent Detection (ED), Non-negative Equivalent Detection, Orthogonal Matching Pursuit (OMP), and Stagewise Orthogonal Matching Pursuit (StOMP). It discusses how each algorithm works, including iteratively selecting atoms from a dictionary to build up a sparse representation of the signal. OMP selects one atom per iteration while StOMP selects all atoms above a threshold. The document also discusses computational complexities of the different algorithms.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
This document summarizes a research paper on the effect of in-band crosstalk for datapath routing in WDM/DWDM networks. It discusses how in-band crosstalk, which occurs when a desired signal and unwanted signals with the same wavelength arrive at a receiver, can degrade signal quality and increase bit error rates. The paper presents a mathematical model to calculate bit error rates and power penalties at the receiver due to component crosstalk from neighboring inputs. Simulation results show that bit error rates increase with higher numbers of interfering channels and crosstalk levels. The paper concludes that receiver noise should be minimized to improve transmission performance through crosstalk reduction.
Wavelet packets provide an adaptive decomposition that overcomes limitations of the discrete wavelet transform (DWT). In wavelet packets, signal decomposition using high-pass and low-pass filters is applied recursively to both low-pass and high-pass outputs, allowing more flexible time-frequency analysis. This results in a redundant dictionary with increased flexibility but also higher computational costs. Pruning algorithms are used to select an optimal subset of bases for a given application based on cost functions related to properties like sparsity, entropy, or energy concentration.
This document discusses using deep neural networks for speech enhancement by finding a mapping between noisy and clean speech signals. It aims to handle a wide range of noises by using a large training dataset with many noise/speech combinations. Techniques like global variance equalization and dropout are used to improve generalization. Experimental results show improvements over MMSE techniques, with the ability to suppress nonstationary noise and avoid musical artifacts. The introduction provides background on speech enhancement, recognition using HMMs and other models, and the role of deep learning advances.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Interstellar Communication Theories and its PossibilitiesIJMER
This paper reviews and discusses the research dimensions in four dimensional time travel and
time dependencies of future and past on the basis of present. The paper investigates the theories that
support time travel in any manner and explore possibilities based on them for interstellar communication
Implementation of Wide Band Frequency Synthesizer Base on DFS (Digital Frequ...IJMER
Wide Band Frequency Synthesizer has become essential components in wireless communication
systems. They are used as frequency synthesizers with precise and convenient digital control in both traditional
electronics, such as televisions and AM/FM radios, and modern consumer products among which cellular
mobile phone is a striking example.
IC fabrication technology advances have made monolithic integration possible. More and more
electronic devices can be put on the same chip to reduce the number of external components and then the costs.
Therefore, on a single chip we can accomplish many functions for which we might need to make several chips
work together a few years ago. A monolithic wide-band PLL is of great interests to wireless communication
applications due to both its low cost and convenience to switch between different communication standards.
The focus of this work is to implement a wide-band Frequency Synthesizer using as few as possible building
blocks and also as simple as possible structure.
While many different product protection measures have been developed and established in
recent years, there is still a great risk posed by the leakage of knowledge in production. These risks are
often downplayed by companies, although they directly relate to their own production and engineering
know-how. The various company-specific protection measures in production span a wide range, and
they can be applied both to production relocation (e.g. to China) and to existing facilities. A systematic
approach for identifying critical damage scenarios, and the methodically supported development and
selection of individual protection measures are required for effective protection of critical company
know-how in production
Men tend to die younger than women for several biological and behavioral reasons. Biologically, men's bodies are less efficient at repairing cellular damage and they lack the protective effects of estrogen. Behaviorally, men are more likely to engage in risky behaviors like smoking, drinking alcohol in excess, not exercising regularly, and dangerous occupations. Addressing behavioral factors through health education and social support could help close the gender gap in life expectancy.
Este documento describe los fundamentos y clasificación de las eflorescencias en ladrillos de construcción. Explica que las eflorescencias son depósitos de sales solubles que aparecen en la superficie de los ladrillos, reduciendo su calidad estética. Los tipos y causas de eflorescencias son diversos y están influenciados por múltiples factores como la migración de sales, la capacidad de absorción de agua del ladrillo, y las condiciones ambientales. Finalmente, detalla las sales solubles más comunes que causan eflorescencias
This document discusses a proposed system for allowing IT professionals to remotely access their office computers from mobile phones using cellular technology. It describes how the system would work, including using SHA-1 encryption to securely transmit data between the mobile device and PC. The system is intended to make remote desktop sharing more convenient and accessible for traveling IT professionals.
Need For Strengthening Automobile Industry in EthiopiaIJMER
This document analyzes the automotive industry in Ethiopia and opportunities to strengthen it. Some key points:
- The automotive sector plays a role in Ethiopia's economy but remains low level due to factors like government regulations, road conditions, purchasing power, lack of skilled labor, and capital shortage.
- Both primary and secondary data were collected and analyzed, finding positive aspects like economic contributions and future growth outweigh negatives.
- It was recommended that further government study is needed to strengthen the automotive industry and support Ethiopia's growth and development.
Stress Analysis of Precast Prestressed Concrete Beams during LiftingIJMER
The use of long span prestressed beams in bridge construction is very common. Even if the
sections are economical the erection of the beam still poses a challenge in construction. Not much work
has been done in the analysis of stress and deflection at erection stage. This paper deals with the
behavior of precast prestressed beams during lifting. Since the spans of these beams are large, it may
fail due to cracking during erection. In this paper a detailed 3-dimensional Finite Element Analysis of 2
prestressed beam sections was done with incorporating the effect of initial imperfections and prestress.
Results were obtained for both prestressed beam and non-prestressed beam and were compared with
Moen’s formulae. To include the effect of prestressing cables in the beam new additional formulae were
introduced and used in combination with the Moen’s. The results obtained were approximately validated
with the Finite Element Analysis results. It is seen that the prestressing cables have a significant effect
on the behavior of a beam during lifting. For a prestressed beam the overhang length should be kept
minimum for safe erection which is opposite in the case of a normal beam.
A Survey of User Authentication Schemes for Mobile DeviceIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
Parametric Analysis and Optimization of Turning Operation by Using Taguchi Ap...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Area Efficient and high-speed fir filter implementation using divided LUT methodIJMER
Traditional method of implementing FIR filters costs considerable hardware resourses,
which goes against the decrease of circuit scale and the increase of system speed. A new design and
implementation of FIR filters using Distributed Arithmetic is provided in this paper to slove this
problem. Distributed Arithmetic structure is used to increase the resourse useage while pipeline
structure is also used to increase the system speed. In addition, the devided LUT method is also used to
decrease the required memory units. The simulation results indicate that FIR filters using Distributed
Arithmetic can work stable with high speed and can save almost 50 percent hardware resourses to
decrease the circuit scale, and can be applied to a variety of areas for its great flexibility and high
reliability
Analysis of Cluster Based Anycast Routing Protocol for Wireless Sensor NetworkIJMER
A wireless sensor network is a collection of nodes organized into a cooperative network.
Each node consists of processing capability, may contain multiple types of memory, have a RF
transceiver, have a power source, and accommodate various sensors and actuators. The nodes
communicate wirelessly and often self-organize after being deployed in an ad hoc fashion.
Routing protocols for wireless sensor networks are responsible for maintaining the routes in the
network and have to ensure reliable multi-hop communication .The performance of the network is
greatly influenced by the routing techniques. Routing is to find out the path to route the sensed data to
the base station. In this paper the features of WSNs are introduced and routing protocols are reviewed
for Wireless Sensor Network.
GPS cycle slips detection and repair through various signal combinationsIJMER
This document discusses methods for detecting and repairing GPS cycle slips. It examines using various combinations of GPS signals as test quantities for detection, including carrier phase observations alone and in combination with pseudorange observations. It finds that graphical detection works for larger slips but statistical tests are superior for detecting smaller slips. For repairing slips, it evaluates using time differences of the original carrier phases and finds that all methods can be used except averaging all data for the first and second differences due to low accuracy. The overall goal is to detect and repair cycle slips to improve positioning accuracy from carrier phase observations.
The document summarizes the European Women Interactive Learning (EWIL) project. The EWIL project aims to stimulate women's motivation to learn and raise the quality of education opportunities for women in non-formal contexts. Specifically, the project aims to allow women to acquire ICT knowledge, promote women's participation in adult learning using culturally relevant content, and help women maximize their ICT skills for personal and professional use. The project receives funding from the Lifelong Learning Programme of the European Union.
The document provides guidelines for assessing lifting, lowering, pushing, pulling and carrying tasks using tables developed by Liberty Mutual based on research conducted by Drs. Stover Snook and Vincent Ciriello. The tables provide population percentages for what percentage of workers can perform certain manual handling tasks based on measurements of weights, distances, heights and frequencies. The tables are intended to help identify risk factors for injury and inform cost-effective ergonomic solutions. Training is recommended for properly using the tables to conduct task analyses and measurements. [END SUMMARY]
A VPN can provide cost savings to organizations by eliminating expensive long-distance leased lines and reducing long-distance phone charges. It also allows easy access to websites and services that may otherwise be restricted. Additionally, VPNs improve network scalability by avoiding the need to purchase dedicated connections between each new office location as a company grows. The document then provides step-by-step instructions for setting up a VPN connection using the SecurityKISS VPN service.
The document investigates the tribological properties of Ni-Cr and Al2O3 13TiO2 coatings deposited via detonation spraying on two types of grey cast iron (GI250 and GIHC). Pin-on-disc wear tests were performed on coated and uncoated samples under different loads. Results show coated samples experienced significantly lower weight loss than uncoated samples. Specifically, the Al2O3 13TiO2 coating on GI250 substrate showed the lowest cumulative weight loss. SEM analysis indicated the coatings were uniform and dense. In conclusion, detonation spraying was effective in depositing wear-resistant coatings on grey iron to reduce wear loss.
This document discusses the challenges faced when using TCP in mobile ad hoc networks (MANETs). Some key challenges include: media access control issues like hidden terminals; power constraints of mobile nodes; frequent topology changes due to node mobility; multipath fading increasing the likelihood of path breaks; and misinterpreting packet losses as congestion rather than broken routes. TCP was designed for wired networks and assumes packet losses are always due to congestion, which does not hold in MANETs where losses can be from broken routes. Overall, TCP performs poorly in MANETs due to these challenges.
This document summarizes a study on the bogie and suspension system of the Indian Railways' WAP-4 electric locomotive. Key points:
- The WAP-4 locomotive was introduced in 1994 to haul heavier passenger trains at higher speeds of up to 140 km/h.
- It has a Co-Co wheel arrangement with 6 traction motors powered by a transformer and silicon rectifiers. The bogies use Flexicoil design with primary and secondary springs suspending the axle boxes and bogie frame.
- Over 800 WAP-4 locomotives are in service. Newer versions have improved diagnostics, static converters, and roof-mounted dynamic brakes. The locomotive can haul
The properties of polynomial hermitian, polynomial normal and polynomial unitary
matrices are discussed. A characterization for polynomial normal matrix is obtained
This document discusses audio compression using multiple transformation techniques for audio applications. It compares the Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) for compressing audio signals. The DCT and DWT are applied to audio signals to generate new data sets with smaller values, achieving compression. Performance is evaluated using metrics like compression ratio, peak signal-to-noise ratio, signal-to-noise ratio, and normalized root mean square error. The results show that DWT provides a lower compression ratio but higher performance metrics compared to DCT. Overall, the document examines using DCT and DWT transforms to compress audio signals and compares their performance.
Isolated words recognition using mfcc, lpc and neural networkeSAT Journals
Abstract Automatic speech recognition is an important topic of speech processing. This paper presents the use of an Artificial Neural Network (ANN) for isolated word recognition. The Pre-processing is done and voiced speech is detected based on energy and zero crossing rates (ZCR). The proposed approach used in speech recognition is Mel Frequency Cepstral Coefficients (MFCC) and combine features of both MFCC and Linear Predictive Coding (LPC). The back-propagation is used as a classifier. The recognition accuracy is increased when combine features of both LPC and MFCC are used as compared to only MFCC approach using Neural Network as a classifier.. Keywords: Pre-processing, Mel frequency Cepstral Coefficient (MFCC), Linear Predictive Coding (LPC), Artificial Neural Network (ANN).
30 9762 extension paper id 0030 (edit i)IAESIJEECS
This paper deals with border distortion effect at starting and ending of finite signal by proposing sliding window technique and basic extension mode implementation. Single phase of transient and voltage sag is chosen to be analyzed in wavelet. The signal which being used for the analysis is simulated in Matlab 2017a. Disturbance signal decomposes into four level and Daubechies 4 (db4) has been chosen for computation. The proposed technique has been compared with conventional method which is finite length power disturbance analysis. Simulation result revealed that the proposed smooth-padding mode can be successfully minimized the border distortion effect compared to the zero-padding and symmetrization
Design and implementation of different audio restoration techniques for audio...eSAT Journals
This document summarizes research on designing and implementing different audio restoration techniques for removing distortions like clipping, clicks, and broadband noise from audio signals. It presents methods for declipping audio using sparse representations and frame-based reconstruction. Clicks are addressed using an adaptive filtering method, and broadband noise is reduced via spectral subtraction. The performance of these techniques is evaluated using metrics like SNR and algorithms like OMP. Hardware implementation of click removal is done on a TMS320C6713 DSK board using tools like MATLAB and Code Composer Studio.
Speech is the vocalizer form of human communication,and based upon the syntactic combination of lexical and vocabularies. The aim of speech coding is to compress the speech signal to the highest possible compression ratio bu t maintaining user acceptability.There are many methods for speech compression like Linear Pre dictive coding (LPC),Code Excited Linear Predictive coding (CELP),Sub-band coding,T ransform coding:- Fast Fourier Transform (FFT),Discrete Cosine Transform (DCT),Continuous Wavelet Transform (CWT),Discrete Wavelet Transform (DWT),Variance Fractal Compression (VFC),Discrete Cosine Transform (DCT),Psychoacoustics and etc. Few of them are discus in this paper.
Recovery of low frequency Signals from noisy data using Ensembled Empirical M...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This document proposes a new approach to compressed image steganography using wavelet transform. The method embeds a compressed payload image within a cover image using discrete wavelet transform (DWT) for image compression and discrete Fourier transform (DFT) to select pixel locations in the cover image. Five test cases of the approach are described and evaluated. In the first case, DWT is applied to the payload image to get 32x32 approximate coefficients, DFT is applied to the cover image to select pixel locations below a threshold, and the coefficients replace the selected pixel values to create the stego-image. The other cases vary the DWT level, threshold value, and image sizes. Results show the stego-image quality
Speech compression analysis using matlabeSAT Journals
This document discusses speech compression analysis using MATLAB. It begins with an introduction to speech compression, noting its importance for efficient storage and transmission of audio data. It then discusses various speech compression techniques, including lossy and lossless compression as well as standards like MPEG. It focuses on using the discrete cosine transform and MATLAB commands to analyze speech signals, including reading wav files, applying windowing functions and the DCT, and playing/viewing the output. The document concludes by discussing current applications of speech compression technologies like MPEG.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Effect of Singular Value Decomposition Based Processing on Speech Perceptionkevig
Speech is an important biological signal for primary mode of communication among human being and also the most natural and efficient form of exchanging information among human in speech. Speech processing is the most important aspect in signal processing. In this paper the theory of linear algebra called singular value decomposition (SVD) is applied to the speech signal. SVD is a technique for deriving important parameters of a signal. The parameters derived using SVD may further be reduced by perceptual evaluation of the synthesized speech using only perceptually important parameters, where the speech signal can be compressed so that the information can be transformed into compressed form without losing its quality. This technique finds wide applications in speech compression, speech recognition, and speech synthesis. The objective of this paper is to investigate the effect of SVD based feature selection of the input speech on the perception of the processed speech signal. The speech signal which is in the form of vowels \a\, \e\, \u\ were recorded from each of the six speakers (3 males and 3 females). The vowels for the six speakers were analyzed using SVD based processing and the effect of the reduction in singular values was investigated on the perception of the resynthesized vowels using reduced singular values. Investigations have shown that the number of singular values can be drastically reduced without significantly affecting the perception of the vowels.
Effect of Singular Value Decomposition Based Processing on Speech Perceptionkevig
Speech is an important biological signal for primary mode of communication among human being and also
the most natural and efficient form of exchanging information among human in speech. Speech processing
is the most important aspect in signal processing. In this paper the theory of linear algebra called singular
value decomposition (SVD) is applied to the speech signal. SVD is a technique for deriving important
parameters of a signal. The parameters derived using SVD may further be reduced by perceptual
evaluation of the synthesized speech using only perceptually important parameters, where the speech signal
can be compressed so that the information can be transformed into compressed form without losing its
quality. This technique finds wide applications in speech compression, speech recognition, and speech
synthesis. The objective of this paper is to investigate the effect of SVD based feature selection of the input
speech on the perception of the processed speech signal. The speech signal which is in the form of vowels
\a\, \e\, \u\ were recorded from each of the six speakers (3 males and 3 females). The vowels for the six
speakers were analyzed using SVD based processing and the effect of the reduction in singular values was
investigated on the perception of the resynthesized vowels using reduced singular values. Investigations
have shown that the number of singular values can be drastically reduced without significantly affecting the
perception of the vowels.
This document summarizes techniques to reduce peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. It first introduces OFDM and discusses how high PAPR is a drawback. It then describes several categories of PAPR reduction techniques: signal distortion techniques like clipping and filtering or peak windowing; signal scrambling techniques like selected mapping, partial transmit sequence, interleaving, tone reservation, and tone injection; and coding techniques like block coding. The document presents simulation results comparing 16-QAM and 64-QAM modulation schemes under various SNR and PAPR levels. It concludes that no single technique achieves large PAPR reduction with high efficiency and low complexity.
An Effective Approach for Colour Image Transmission using DWT Over OFDM for B...IJMTST Journal
Image transmission over the fading channels without degrading the perceptual quality is a challenging task while mitigating the power consumption in many fields such as broadband networks, mobile communications, Image sharing and video broadcasting. Also, it is not possible to resend the lost packets every time in many applications such as video broadcasting. Here, an effective approach for color image transmission has been proposed with power saving approach over OFDM system. Experimental results shows that the reception quality of received image is good enough with various peak signal to noise ratios also saved 60% of energy.
This document summarizes a research paper that proposes a new speech coding technique to compress speech at low bit rates while maintaining quality. The technique uses a sinusoidal representation where speech frames are represented as the sum of sinusoidal components. The encoder analyzes speech frames in the frequency domain using short-time Fourier transform. It extracts peak amplitudes, frequencies, and phases using peak-picking. It then applies novel parameter reduction and quantization techniques to lower the bit rate, including dividing frames into voiced/unvoiced sub-frames and prioritizing more important peaks. The decoder reconstructs speech from the transmitted parameters. The technique aims to achieve high quality reconstruction at low bit rates for applications requiring efficient digital speech storage and transmission.
Performance evaluation on the basis of bit error rate for different order of ...ijmnct
This document summarizes research evaluating the bit error rate (BER) for different modulation orders and subchannel lengths in an orthogonal frequency division multiplexing (OFDM) system. The research considers QPSK, 8-QAM, and 16-QAM modulation with 256, 512, and 4096 subchannels. Simulation results in MATLAB show that:
1) For 256 subchannels, QPSK modulation has the lowest BER across signal-to-noise ratio (SNR) values from 0-27dB.
2) BER increases with higher modulation orders (from QPSK to 16-QAM) for a given subchannel length.
3) The research provides a comparative analysis of BER performance in an OFDM system
This document discusses a redundancy removal technique for real-time voice compression. It begins by introducing voice compression and its increasing popularity. It then describes implementing a redundancy removal technique using MATLAB to encode and compress speech in real-time. The technique accurately estimates speech parameters and is computationally efficient. Testing showed it provided high compression and high quality audio. The technique reduces bandwidth needs for voice traffic, providing better performance than other methods for real-time applications.
Ijaems apr-2016-30 Digital Audio Watermarking using EMD for Voice Message Enc...INFOGAIN PUBLICATION
Several accurate watermarking methods for image watermarking have being suggested and implemented to secure various forms of digital data, images and videos however, very few algorithms are proposed for audio watermarking. This is also because human audio system has dynamic range which is wider in comparison with human vision system. In this paper, a new audio watermarking algorithm for voice message encryption based on Empirical Mode Decomposition (EMD) is introduced. The audio signal is divided into frames and each frame is then decomposed adaptively, by EMD, into intrinsic oscillatory components called Intrinsic Mode Functions (IMFs). The watermark, which is the secret message that is to be sent, along with the synchronization codes are embedded into the extrema of the last IMF, a low frequency mode stable under different attacks and preserving the perceptual quality of the host signal. Based on exhaustive simulations, we show the robustness of the hidden watermark for audio compression, false decryption, re-quantization, resampling. The comparison analysis shows that our method has better performance than other steganography schemes recently reported.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
DATA HIDING IN AUDIO SIGNALS USING WAVELET TRANSFORM WITH ENHANCED SECURITYcsandit
Rapid increase in data transmission over internet results in emphasis on information security.
Audio steganography is used for secure transmission of secret data with audio signal as the
carrier. In the proposed method, cover audio file is transformed from space domain to wavelet
domain using lifting scheme, leading to secure data hiding. Text message is encrypted using
dynamic encryption algorithm. Cipher text is then hidden in wavelet coefficients of cover audio
signal. Signal to Noise Ratio (SNR) and Squared Pearson Correlation Coefficient (SPCC)
values are computed to judge the quality of the stego audio signal. Results show that stego
audio signal is perceptually indistinguishable from the cover audio signal. Stego audio signal is
robust even in presence of external noise. Proposed method provides secure and least error
data extraction.
A Study on Translucent Concrete Product and Its Properties by Using Optical F...IJMER
- Translucent concrete is a concrete based material with light-transferring properties,
obtained due to embedded light optical elements like Optical fibers used in concrete. Light is conducted
through the concrete from one end to the other. This results into a certain light pattern on the other
surface, depending on the fiber structure. Optical fibers transmit light so effectively that there is
virtually no loss of light conducted through the fibers. This paper deals with the modeling of such
translucent or transparent concrete blocks and panel and their usage and also the advantages it brings
in the field. The main purpose is to use sunlight as a light source to reduce the power consumption of
illumination and to use the optical fiber to sense the stress of structures and also use this concrete as an
architectural purpose of the building
Developing Cost Effective Automation for Cotton Seed DelintingIJMER
A low cost automation system for removal of lint from cottonseed is to be designed and
developed. The setup consists of stainless steel drum with stirrer in which cottonseeds having lint is mixed
with concentrated sulphuric acid. So lint will get burn. This lint free cottonseed treated with lime water to
neutralize acidic nature. After water washing this cottonseeds are used for agriculter purpose
Study & Testing Of Bio-Composite Material Based On Munja FibreIJMER
The incorporation of natural fibres such as munja fiber composites has gained
increasing applications both in many areas of Engineering and Technology. The aim of this study is to
evaluate mechanical properties such as flexural and tensile properties of reinforced epoxy composites.
This is mainly due to their applicable benefits as they are light weight and offer low cost compared to
synthetic fibre composites. Munja fibres recently have been a substitute material in many weight-critical
applications in areas such as aerospace, automotive and other high demanding industrial sectors. In
this study, natural munja fibre composites and munja/fibreglass hybrid composites were fabricated by a
combination of hand lay-up and cold-press methods. A new variety in munja fibre is the present work
the main aim of the work is to extract the neat fibre and is characterized for its flexural characteristics.
The composites are fabricated by reinforcing untreated and treated fibre and are tested for their
mechanical, properties strictly as per ASTM procedures.
Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)IJMER
Hybrid engine is a combination of Stirling engine, IC engine and Electric motor. All these 3 are
connected together to a single shaft. The power source of the Stirling engine will be a Solar Panel. The aim of
this is to run the automobile using a Hybrid engine
Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...IJMER
This document summarizes research on the fabrication and characterization of bio-composite materials using sunnhemp fibre. The document discusses how sunnhemp fibre was used to reinforce an epoxy matrix through hand lay-up methods. Various mechanical properties of the bio-composites were tested, including tensile, flexural, and impact properties. The results of the mechanical tests on the bio-composite specimens are presented. Potential applications of the sunnhemp fibre bio-composites are also suggested, such as in fall ceilings, partitions, packaging, automotive interiors, and toys.
Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...IJMER
The Greenstone belts of Karnataka are enriched in BIFs in Dharwar craton, where Iron
formations are confined to the basin shelf, clearly separated from the deeper-water iron formation that
accumulated at the basin margin and flanking the marine basin. Geochemical data procured in terms of
major, trace and REE are plotted in various diagrams to interpret the genesis of BIFs. Al2O3, Fe2O3 (T),
TiO2, CaO, and SiO2 abundances and ratios show a wide variation. Ni, Co, Zr, Sc, V, Rb, Sr, U, Th,
ΣREE, La, Ce and Eu anomalies and their binary relationships indicate that wherever the terrigenous
component has increased, the concentration of elements of felsic such as Zr and Hf has gone up. Elevated
concentrations of Ni, Co and Sc are contributed by chlorite and other components characteristic of basic
volcanic debris. The data suggest that these formations were generated by chemical and clastic
sedimentary processes on a shallow shelf. During transgression, chemical precipitation took place at the
sediment-water interface, whereas at the time of regression. Iron ore formed with sedimentary structures
and textures in Kammatturu area, in a setting where the water column was oxygenated.
Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...IJMER
In this paper, the mechanical characteristics of C45 medium carbon steel are investigated
under various working conditions. The main characteristic to be studied on this paper is impact toughness
of the material with different configurations and the experiment were carried out on charpy impact testing
equipment. This study reveals the ability of the material to absorb energy up to failure for various
specimen configurations under different heat treated conditions and the corresponding results were
compared with the analysis outcome
Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...IJMER
Robot guns are being increasingly employed in automotive manufacturing to replace
risky jobs and also to increase productivity. Using a single robot for a single operation proves to be
expensive. Hence for cost optimization, multiple guns are mounted on a single robot and multiple
operations are performed. Robot Gun structure is an efficient way in which multiple welds can be done
simultaneously. However mounting several weld guns on a single structure induces a variety of
dynamic loads, especially during movement of the robot arm as it maneuvers to reach the weld
locations. The primary idea employed in this paper, is to model those dynamic loads as equivalent G
force loads in FEA. This approach will be on the conservative side, and will be saving time and
subsequently cost efficient. The approach of the paper is towards creating a standard operating
procedure when it comes to analysis of such structures, with emphasis on deploying various technical
aspects of FEA such as Non Linear Geometry, Multipoint Constraint Contact Algorithm, Multizone
meshing .
Static Analysis of Go-Kart Chassis by Analytical and Solid Works SimulationIJMER
This paper aims to do modelling, simulation and performing the static analysis of a go
kart chassis consisting of Circular beams. Modelling, simulations and analysis are performed using 3-D
modelling software i.e. Solid Works and ANSYS according to the rulebook provided by Indian Society of
New Era Engineers (ISNEE) for National Go Kart Championship (NGKC-14).The maximum deflection is
determined by performing static analysis. Computed results are then compared to analytical calculation,
where it is found that the location of maximum deflection agrees well with theoretical approximation but
varies on magnitude aspect.
In récent year various vehicle introduced in market but due to limitation in
carbon émission and BS Séries limitd speed availability vehicle in the market and causing of
environnent pollution over few year There is need to decrease dependancy on fuel vehicle.
bicycle is to be modified for optional in the future To implement new technique using change in
pedal assembly and variable speed gearbox such as planetary gear optimise speed of vehicle
with variable speed ratio.To increase the efficiency of bicycle for confortable drive and to
reduce torque appli éd on bicycle. we introduced epicyclic gear box in which transmission done
throgh Chain Drive (i.e. Sprocket )to rear wheel with help of Epicyclical gear Box to give
number of différent Speed during driving.To reduce torque requirent in the cycle with change in
the pedal mechanism
Integration of Struts & Spring & Hibernate for Enterprise ApplicationsIJMER
This document discusses integrating the Spring, Struts, and Hibernate frameworks to develop enterprise applications. It provides an overview of each framework and their features. The Spring Framework is a lightweight, modular framework that allows for inversion of control and aspect-oriented programming. It can be used to develop any or all tiers of an application. The document proposes an architecture for an e-commerce website that integrates these three frameworks, with Spring handling the business layer, Struts the presentation layer, and Hibernate the data access layer. This modular approach allows for clear separation of concerns and reduces complexity in application development.
Microcontroller Based Automatic Sprinkler Irrigation SystemIJMER
Microcontroller based Automatic Sprinkler System is a new concept of using
intelligence power of embedded technology in the sprinkler irrigation work. Designed system replaces
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IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
Speech Compression Using Wavelets
1. International
OPEN ACCESS Journal
Of Modern Engineering Research (IJMER)
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 4 | Apr. 2014 | 32 |
Speech Compression Using Wavelets
P. srinivasa rao1
, G.krishnaveni2
, G. Prasanna kumar 3
, G.satyanandam4
,
CH.parimala5
, K.ramteja6
1
(Department of Electronics & Communication Engineering, Asst.professor, St.Ann’s college of engineering &
technology, India)
2, 3, 4, 5, 6
(Department of Electronics & Communication Engineering ,Student, St.Ann’s college of engineering &
technology, India)
I. Introduction
Speech Compression is a method to convert human speech into an encoded form in such a way that it
can later be decoded to get back the original signal .Compression is basically to remove redundancy between
neighboring samples and between adjacent cycles. Major objective of speech compression is to represent signal
with lesser number of bits. The reduction of data should be done in such a way that there is acceptable loss of
quality.
II. Compression
Compression is a process of converting an input data stream into another data stream that has a smaller
size. Compression is possible only because data is normally represented in the computer in a format that is
longer than necessary i.e. the input data has some amount of redundancy associated with it. The main objective
of compression systems is to eliminate this redundancy. When compression is used to reduce storage
requirements, overall program execution time may be reduced. This is because reduction in storage will result in
the reduction of disc access attempts. With respect to transmission of data, the data rate is reduced at the source
by the compressor (coder) ,it is then passed through the communication channel and returned to the original rate
by the expander(decoder) at the receiving end. The compression algorithms help to reduce the bandwidth
requirements and also provide a level of security for the data being transmitted. A tandem pair of coder and
decoder is usually referred to as codec.
2.1 Types of compression
There are mainly two types of compression techniques - Lossless Compression and Lousy Compression.
2.1.1 Lossless compression
It is a class of data compression algorithm that allows the exact original data to be reconstructed from
the exact original data to be reconstructed from the compressed data. It is mainly used in cases where it is
important that the original signal and the decompressed signal are almost same or identical. Examples of lossless
compression are Huffman coding.
2.1.2 Lousy compression
It is a data encoding method that compresses data by removing some of them. The aim of this
technique is to minimize the amount of data that has to be transmitted. They are mostly used for multimedia data
compression. The rest of the paper is organized as follow; section 2 gives the Theoretical background about the
speech compression schemes. The speech compression techniques are described in section 3& Section 4
evaluates the performance of the proposed technique followed by the conclusion.
Abstract: In the recent years, large scale information transfer by remote computing and the development
of massive storage and retrieval systems have witnessed a tremendous growth. To cope up with the
growth in the size of databases, additional storage devices need to be installed and the modems and
multiplexers have to be continuously upgraded in order to permit large amounts of data transfer between
computers and remote terminals. This leads to an increase in the cost as well as equipment. One solution
to these problems is “COMPRESSION” where the database and the transmission sequence can be
encoded efficiently. In this we investigated for optimum wavelet, optimum level, and optimum scaling
factor.
2. Speech compression using wavelets
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 4 | Apr. 2014 | 33 |
III. Techniques for speech compression
Speech compression is classified into three categories,
3.1 Waveform coding
The signal that is transmitted as input is tried to be reproduced at the output which would be very
similar to the original signal.
3.2 Parametric coding
In this type of coding the signals are represented in the form of small parameters which describes the
signals very accurately. In parametric extraction method a preprocessor is used to extract some features that can
be later used to extract the original signal.
3.3 Transform coding
This is the coding technique that we have used for our paper. In this method the signal is transformed
into frequency domain and then only dominant feature of signal is maintained. In transform method we have
used discrete wavelet transform technique and discrete cosine transform technique. When we use wavelet
transform technique, the original signal can be represented in terms of wavelet expansion.
Similarly in case of DCT transform speech can be represented in terms of DCT coefficients.
Transform techniques do not compress the signal, they provide information about the signal and using various
encoding techniques compressions of signal is done. Speech compression is done by neglecting small and lesser
important coefficients and data and discarding them and then using quantization and encoding techniques.
Speech compression is performed in the following steps.
1. Transform technique
2. Thresholding of transformed coefficients
3. Quantization
4. Encoding
3.3.1 Transform technique
DCT and DWT methods are used on speech signal. Using DCT, reconstruction of signal can be done
very accurately; this property of DCT is used for data compression. Localization feature of wavelet along with
time frequency resolution property makes DWT very suitable for speech compression. The main idea behind
signal compression using wavelets is linked primarily to the relative scarceness of the wavelet domain
representation of signal.
A) Continuous wavelet transforms (CWT)
This chapter provides a motivation towards the study of wavelets as a tool for signal processing. The
drawbacks inherent in the Fourier methods are overcome with wavelets. This fact is demonstrated here.
It must be reiterated that the discussion in this chapter is by no means comprehensive and exhaustive. The
concepts of time-frequency resolution have been avoided for the sake of simplicity. Instead, the development
endeavors to compare the Wavelet methods with the Fourier methods as the reader is expected to be well
conversant with the latter.
Consider the following figure which juxtaposes a sinusoid and a wavelet
Fig 3.1: comparing sine wave and a wavelet
As has already been pointed out, wavelet is a waveform of effectively limited duration
That has an average value of zero. Compare wavelets with sine waves, which are the basis of Fourier analysis.
Sinusoids do not have limited duration -- they extend from minus to plus infinity. And where sinusoids are
smooth and predictable, wavelets tend to be irregular and asymmetric.
Fourier analysis consists of breaking up a signal into sine waves of various Frequencies. Similarly, wavelet
analysis is the breaking up of a signal into shifted and scaled versions of the original (or mother) wavelet.
3. Speech compression using wavelets
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 4 | Apr. 2014 | 34 |
Fig3.2: constituent wavelets of different scales and positions
The above diagram suggests the existence of a synthesis equation to represent the original signal as a
linear combination of wavelets which are the basis function for wavelet analysis (recollect that in Fourier
analysis, the basic functions are sines and cosines). This is indeed the case. The wavelets in the synthesis
equation are multiplied by scalars. To obtain these scalars, we need an analysis equation, just as in the Fourier
case. We thus have two equations, the analysis and the synthesis equation. They are stated as follows:
1. Analysis equation or CWT equation:
𝐶 𝑎, 𝑏 = 𝑓 𝑡 .
1
|𝑎|
ᴪ
∞
−∞
∗
𝑡−𝑏
𝑎
𝑑 𝑡 … … … (3.1)
2. Synthesis equation or ICWT:
𝑓 𝑡 =
1
𝐾
1
|𝑎|2
∞
𝑏=−∞
∞
𝑎=−∞
𝐶 𝑎, 𝑏
1
𝑎
ᴪ
t − b
a
. 𝑑 𝑎 . 𝑑 𝑏 … … … … (3.2)
B) Continuous-time Wavelet
Consider a real or complex-valued continuous-time function y(t) with the following Properties:
1. The function integrates to zero
ᴪ 𝑡 . 𝑑 𝑡 = 0 … … … … (3.3)
∞
−∞
2. It is square integrable or, equivalently, has finite energy
|ᴪ(𝑡)|2
∞
−∞
. 𝑑 𝑡 < ∞ … … … … (3.4)
Fig3.3: some wavelet functions
4. Speech compression using wavelets
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 4 | Apr. 2014 | 35 |
C) Discrete wavelet transforms (DWT)
A discrete wavelet transform can be defined as a „small wave‟ that has its energy concentrated in time,
and it provides a tool for the analysis of transient, non-stationary or time varying phenomenon. It has oscillating
wave like property. Wavelet is a waveform of limited duration having an average value zero. They are localized
in space. Wavelet transform provides a time-frequency representation of the signal. In DWT, the signal is
decomposed into set of basic functions also known as „WAVELETS‟. Wavelets are obtained from a single
MOTHER WAVELET by delay and shift in.
𝛹 𝑡 =
1
𝑎
ᴪ
(𝑡−𝑏)
𝑎
… … … … (3.5)
Where ‟a‟ is the scaling parameter and „b‟ is the shifting parameter.DWT uses multi resolution
technique to analyze different frequencies. In DWT, the prominent information in the signal appears in the
lower amplitudes. Thus compression can be achieved by discarding the low amplitude signals.
D) Discrete cosine transforms (DCT)
Discrete Cosine Transform can be used for speech compression because of high correlation in adjacent
coefficient. We can reconstruct a sequence very accurately from very few DCT coefficients. This property of
DCT helps in effective reduction of data.
DCT of 1-D sequence x (n) of length N is given by
𝑋 𝑚 = [
2
𝑁
]1/2
𝐶 𝑚 𝑋 𝑛 cos[
2𝑛+1 𝑚𝜋
2𝑁
𝑁−1
𝑚=0 ]…………………..(3.6)
Where m=0, 1, - - - - - -, N-1
The inverse discrete cosine transform is
𝑋 𝑛 = [
2
𝑁
]1/2
𝐶𝑚 𝑋 𝑚 cos[
2𝑛+1 𝑚𝜋
2𝑁
]𝑁−1
𝑚=0 …………………..(3.7)
In both equations Cm can be defined as
Cm= (1/2)1/2 for m=0.
=1form≠0
3.3.2 Thresholding
After the coefficients are received from different transforms, thresholding is done. Very few DCT
coefficients represent 99% of signal energy; hence Thresholding is calculated and applied to the coefficients.
Coefficients having values less than threshold values are removed.
3.3.3 Quantization
It is a process of mapping a set of continuous valued data to a set of discrete valued data. The aim of
quantization is to reduce the information found in threshold coefficients. This process makes sure that it
produces minimum errors. We basically perform uniform quantization process.
3.3.4 Encoding
We use different encoding techniques like Run Length Encoding and Huffman Encoding. Encoding
method is used to remove data that are repetitively occurring. In encoding we can also reduce the number of
coefficients by removing the redundant data. Encoding can use any of the two compression techniques, lossless
or lossy. This helps in reducing the bandwidth of the signal hence compression can be achieved. The
compressed speech signal can be reconstructed to form the original signal by decoding followed by
dequantization and then performing the inverse-transform methods. This would reproduce the original signal.
IV. Weaknesses of Fourier analysis
This chapter develops the need and motivation for studying the wavelet transform. Historically,
Fourier Transform has been the most widely used tool for signal processing. As signal processing began
spreading its tentacles and encompassing newer signals, Fourier Transform was found to be unable to satisfy the
growing need for processing a bulk of signals. Hence, this chapter begins with a review of Fourier Methods
Detailed explanation is avoided to rid the discussion of insignificant details. A simple case is presented, where
the shortcomings of Fourier methods is expounded. The next chapter concerns wavelet transforms, and shows
how the drawback of FT is eliminated.
4.1 Review of Fourier Methods
For a continuous –time signal x(t) , the Fourier Transform (FT) equations are
𝑋 𝑓 = 𝑥 𝑡 . 𝑒−2𝑗𝜋𝑓𝑡
𝑑𝑡
∞
−∞
………..(4.1)
𝑥 𝑡 = 𝑋 𝑓 . 𝑒2𝑗𝜋𝑓𝑡∞
−∞
𝑑𝑓…………(4.2)
Equation (2.1) is the analysis equation and equation (2.2) is the synthesis equation.
5. Speech compression using wavelets
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 4 | Apr. 2014 | 36 |
The synthesis equation suggests that the FT expresses the signal in terms of linear combination of
complex exponential signal. For a real signal, it can be shown that the FT synthesis equation expresses the
signal in terms of linear combination of sine and cosine terms.
Fig 4.1: constituent sinusoids of different frequencies
The analysis equation represents the given signal in a different form; as a function of frequency. The
original signal is a function of time, whereas the after the transformation, the same signal is represented as a
function of frequency. It gives the frequency components
Fig4.2: Fourier transform
Thus the FT is a very useful tool as it gives the frequency content of the input signal. It however suffers
from a serious drawback. It is explained through an example in the sequel.
4.2 Shortcomings of FT
Ex: 2.1- Consider the following 2 signals
x1(t) = sin(2*p*100*t) 0 <= t < 0.1 sec
= sin(2*p*500*t) 0.1 <= t < 0.2 sec
x2(t) = sin(2*p*500*t) 0 <= t < 0.1 sec
= sin(2*p*100*t) 0.1 <= t < 0.2 sec
A plot of these signals is shown below.
(Note: A time interval of 0 to 0.2 seconds was divided into 10,000 points. The sine of each point was
computed and plotted. Since the signal is of 10,000 points, 16,384 point FFT was computed which represents
the frequency domain of the signal.)
Fig4.3:signalX1 (t) and its FFT
6. Speech compression using wavelets
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 4 | Apr. 2014 | 37 |
Fig4.4:signalX2 (t) and its FFT
The above example demonstrates the drawback inherent in the Fourier analysis of signals. It shows that
the FT is unable to distinguish between two different signals. The two signals have same of giving time
information of signals.
In general, FT is not suitable for the analysis of a class of signals called “Non stationary signals”. This
led to the search of new tools for analysis of signals. One such tool that was proposed was the “Short time
Fourier transforms” (STFT). This STFT too suffered from a drawback1 and was supplanted by “Wavelet
transform”.
V. Procedure
5.1 Wavelet based compression techniques
Wavelets concentrate speech signals into a few neighboring coefficients. By taking the wavelet
transform of a signal, many of its‟ coefficients will either be zero or have negligible magnitudes. Data
compression can then be done by treating the small valued coefficients as insignificant data and discarding
them. Compressing a speech signal using wavelets involves the following stages.
5.2Choice of wavelets
Choosing mother-wavelet function which is used in designing high quality speech coders is of prime
importance. Choosing a wavelet having a compact support in time and frequency in addition to a significant
number of vanishing moments is important for wavelet speech compressor. Different criteria can be used in
selecting an optimal wavelet function. The objective is to minimize the error variance and maximize signal to
noise ratio. They can be selected based on the energy conservation properties. Better reconstruction quality is
provided by wavelets with more vanishing moments, as they introduce lesser distortion and concentrate more
signal energy in neighboring coefficients.
However the computational complexity of DWT increases with the number of vanishing moments.
Hence it is not practical to use wavelets with higher number of vanishing moments. Number of vanishing
moments of a wavelet indicates the smoothness of a wavelet function and also the flatness of the frequency
response of the wavelet filters. Higher the number of vanishing moments, faster is the decay rate of wavelet
coefficients. It leads to a more compact signal representation and hence useful in coding applications. However,
length of the filters increases with the number of vanishing moments and the hence complexity of computing the
DWT coefficients increases.
5.3 Decomposition of wavelets
Wavelets decompose a signal into different resolutions or frequency bands. Signal compression is
based on the concept that selecting small number of approximation coefficients and some of the detail
coefficients can represent the signal components accurately. Choosing a decomposition level for the DWT
depends on the type of signal being used or parameters like entropy.
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5.4 Truncation of coefficients
Compression involves truncating wavelet coefficients below threshold. Most of the speech energy is
high-valued coefficient. Thus the small valued coefficients can be truncated or zeroed and can then be used for
reconstruction of the signal. This compression technique provided lesser signal-to-noise ratio.
.
5.5 Encoding coefficients
Signal compression is achieved by first truncating small-valued coefficients and then encoding these
coefficients. High-magnitude coefficients can be represented by storing the coefficients along with their
respective positions in the wavelet transform vector. Another method for compression is to encode consecutive
zero valued coefficient with two bytes. One byte indicates the sequence of zeros in the wavelet transforms
vector and the second byte represents the number of consecutive zeros. For further data compression a suitable
bit-encoding format can be used. Low bit rate representation of signal can be achieved by using an entropy
coder like Huffman coding.
5.6 Calculating threshold
Two different thresholding techniques are used for the truncation of coefficients i.e. global thresholding
and level thresholding.
Global Thresholding- It takes the wavelet expansion of the signal and keeps the largest absolute value
coefficient. In this we manually set a global threshold. Hence only a single parameter needs to be
selected in this case.
Level Thresholding- It applies visually determined level dependent thresholds to each of the
decomposition level in the wavelet transform.
5.7 Encoding zero value functions
In this method, consecutive zero valued coefficients are encoded with two bytes. One byte specifies the
starting string of zeros and the second byte keeps record of the number of successive zeros. This encoding
method provides a higher compression ratio.
VI. DCT based compression technique
The given sound file is read. The vector is divided into smaller frames and arranged into matrix form.
DCT operation is performed on the matrix. DCT operation is performed and the elements are sorted in their
matrix form to find components and their indices.
The elements are arranged in descending order. After the arrangement has been done, a Threshold
value is decided. The coefficients below the threshold values are discarded. Hence reducing the size of the
signal which results in compression. The data is then converted back into the original form by using
reconstruction process. For this we perform IDCT operation on the signal. Now convert the signal back to its
vector form. Thus the signal is reconstructed.
VII. Applications of compression
1. The use of compression in recording applications is extremely powerful. The playing time of the medium
is extended in proportion to the compression factor.
2. In the case of tapes, the access time is improved because the length of the tape needed for a given
recording is reduced and so it can be rewound more quickly.
3. In digital audio broadcasting and in digital television transmission, compression is
Used to reduce the bandwidth needed.
4. The time required for a web page to be displayed and the downloading time in case of files is greatly
reduced due to compression.
VIII. Compression terminology
Compression ratio:- The compression ratio is defined as
Compression ratio = size of the output stream/size of the input stream. A value of 0.6 means that the data
occupies 60% of its original size after compression. Values greater than 1 mean an output stream bigger
than the input stream. The compression ratio can also be called bpb(bit per bit),since it equals the no. of
bits in the compressed stream needed, on an average, to compress one bit in the input stream.
Compression factor:- It is the inverse of compression ratio. Values greater than 1 indicate compression and
less than 1 indicates expansion
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8.1 Aim, scope and limitations of this thesis
The primary objective of this thesis is to present the wavelet based method for the compression of
speech. The algorithm presented here was implemented in MATLAB the said software is provided in the
accompanying CD. Readers may find it useful to verify the result by running the program
Since this thesis is an application of wavelets, it was natural to study the basics of wavelets in detail. The same
procedure was adopted in writing this thesis, as it was felt 5 that without minimal background in wavelets, it
would be fruitless, and also inconvenient to explain the algorithm.
However, the wavelet itself is an engrossing field, and a comprehensive study was beyond the scope of
our undergraduate level. Hence, attempt is made only to explain the very basics which are indispensable from
the compression point of view.
This approach led to the elimination of many of the mammoth sized equations and vector analysis
inherent in the study of wavelets.
At this stage, it is worthwhile mentioning two quotes by famous scientists
„So far as the laws of mathematics refer to reality, they are not certain. And so far as they are certain, they do
not refer to reality.‟ --Albert Einstein „As complexity rises, precise statements lose meaning and meaningful
statements lose precision.‟ --Lotfi Zadeh 1
The inclusion of the above quotes is to highlight the fact that simplicity and clarity are often the
casualties of precision and accuracy, and vice-versa.
In this thesis, we have compromised on the mathematical precision and accuracy to make matters simple and
clear. An amateur in the field of wavelets might find this work useful as it is relieved of most of the intimidating
vector analysis and equations, which have been supplanted by simple diagrams. However, for our own
understanding, we did found it necessary, interesting and exciting to go through some literature which deal with
the intricate details of wavelet analysis, and sufficient references have been provided wherever necessary, for
the sake of a fairly advanced reader. Some of the literature that we perused has been included in the CD.
The analysis that we undertook for wavelets includes only the orthogonal wavelets. This decision was
based on the extensive literature we read on the topic, wherein the suitability of these wavelets for speech
signals was stated. Another topic that has been deliberately excluded in this work is the concept of MRA, which
bridges the gap between the wavelets and the filter banks and is indispensable for a good understanding of
Mallet‟s Fast Wavelet Transform Algorithm. Instead, we have assumed certain results and provided references
for further reading.
Secondly, the sound files that we tested were of limited duration, around 5 seconds. Albeit the
programs will run for larger files (of course, the computation time will be longer in this case), a better approach
towards such large files is to use frames of finite length. This procedure is more used in real-time compression
of sound files, and is not presented here.
Encoding is performed using only the Run Length Encoding. The effect of other encoding schemes on
the compression factor has not been studied.
This thesis considers only wavelets analysis, wherein only approximation coefficients are split. There exists
another analysis, called wavelet packet analysis, which splits detail coefficients. This is not explored in this
thesis.
IX. Conclusion and future scope
In this project compress the data by optimization of wavelet, scale, and level. This technology is
needed in the field of speech to satisfy transfer requirements of huge speech signals via communication
companies and decreasing storage equipment is another need.
The main objective was to develop an appreciation for wavelet transforms, discuss their application in
compression of human speech signals and study the effect of a few parameters on the quality of compression.
The parameters studied are: Sampling frequency, type of wavelet, threshold, file. Here using only hear,
daubechies wavelets etc, if apply the advanced wavelets like biorthogonal wavelets achieve better performance.
Encoding is performed using only the Run Length Encoding. Higher compression ratios are expected
with coding techniques like Huffman coding
REFERENCES
[1.] Robi Polikar,”The Wavelet Tutorial Part I, Part II and Part III”.
[2.] J. Pang, S.Chauhan,”FPGA Design of Speech
[3.] Compression Using DWT” Proceeding of World
[4.] Congress on Engineering and Computer science October 22-24, 2008, San Francisco, USA.
[5.] Fundamentals of speech recognition by Lawrence Rabiner.