This document describes the design of a Punjabi speech synthesis system using Hidden Markov Models. It discusses collecting Punjabi text from various domains to build a speech corpus. Features are extracted from the text and stored in a database. The system has offline and online phases, where the database is created offline and text-to-speech conversion occurs online. Hidden Markov Models are used for statistical parametric speech synthesis, modeling acoustic features like fundamental frequency, duration, and spectrum. The system breaks text into phonetic units like phonemes and diphones to generate waveforms for natural-sounding synthesized speech.
Performance Calculation of Speech Synthesis Methods for Hindi languageiosrjce
The document compares the performance of two speech synthesis methods - unit selection and hidden Markov model (HMM) - for Hindi language. It finds that unit selection results in higher quality synthesized speech than HMM based on both subjective and objective quality measurements. Subjective measurements using mean opinion scores show unit selection receives higher average ratings. Objective measurements of mean square error and peak signal-to-noise ratio also indicate unit selection introduces less distortion compared to the original speech samples.
Limited Data Speaker Verification: Fusion of FeaturesIJECEIAES
The present work demonstrates experimental evaluation of speaker verification for dif- ferent speech feature extraction techniques with the constraints of limited data (less than 15 seconds). The state-of-the-art speaker verification techniques provide good performance for sufficient data (greater than 1 minutes). It is a challenging task to develop techniques which perform well for speaker verification under limited data condition. In this work different features like Mel Frequency Cepstral Coefficients (MFCC), Linear Prediction Cepstral Coefficients (LPCC), Delta (4), Delta-Delta (44), Linear Prediction Residual (LPR) and Linear Prediction Residual Phase (LPRP) are considered. The performance of individual features is studied and for better verification performance, combination of these features is attempted. A comparative study is made between Gaussian mixture model (GMM) and GMM-universal background model (GMM-UBM) through experimental evaluation. The experiments are conducted using NIST-2003 database. The experimental results show that, the combination of features provides better performance compared to the individual features. Further GMM-UBM modeling gives reduced equal error rate (EER) as compared to GMM.
A Marathi Hidden-Markov Model Based Speech Synthesis Systemiosrjce
IOSR journal of VLSI and Signal Processing (IOSRJVSP) is a double blind peer reviewed International Journal that publishes articles which contribute new results in all areas of VLSI Design & Signal Processing. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced VLSI Design & Signal Processing concepts and establishing new collaborations in these areas.
Design and realization of microelectronic systems using VLSI/ULSI technologies require close collaboration among scientists and engineers in the fields of systems architecture, logic and circuit design, chips and wafer fabrication, packaging, testing and systems applications. Generation of specifications, design and verification must be performed at all abstraction levels, including the system, register-transfer, logic, circuit, transistor and process levels
Speech to text conversion for visually impaired person using µ law compandingiosrjce
The paper represents the overall design and implementation of DSP based speech recognition and
text conversion system. Speech is usually taken as a preferred mode of operation for human being, This paper
represent voice oriented command for converting into text. We intended to compute the entire speech processing
in real time. This involves simultaneously accepting the input from the user and using software filters to analyse
the data. The comparison was then to be established by using correlation and µ law companding techniques. In
this paper, voice recognition is carried out using MATLAB. The voice command is a person independent. The
voice command is stored in the data base with the help of the function keys. The real time input speech received
is then processed in the speech recognition system where the required feature of the speech words are extracted,
filtered out and matched with the existing sample stored in the database. Then the required MATLAB processes
are done to convert the received data and into text form.
Hindi digits recognition system on speech data collected in different natural...csandit
This paper presents a baseline digits speech recognizer for Hindi language. The recording environment is different for all speakers, since the data is collected in their respective homes. The different environment refers to vehicle horn noises in some road facing rooms, internal background noises in some rooms like opening doors, silence in some rooms etc. All these recordings are used for training acoustic model. The Acoustic Model is trained on 8 speakers’ audio data. The vocabulary size of the recognizer is 10 words. HTK toolkit is used for building
acoustic model and evaluating the recognition rate of the recognizer. The efficiency of the recognizer developed on recorded data, is shown at the end of the paper and possible directions for future research work are suggested.
Approach of Syllable Based Unit Selection Text- To-Speech Synthesis System fo...iosrjce
IOSR journal of VLSI and Signal Processing (IOSRJVSP) is a double blind peer reviewed International Journal that publishes articles which contribute new results in all areas of VLSI Design & Signal Processing. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced VLSI Design & Signal Processing concepts and establishing new collaborations in these areas.Design and realization of microelectronic systems using VLSI/ULSI technologies require close collaboration among scientists and engineers in the fields of systems architecture, logic and circuit design, chips and wafer fabrication, packaging, testing and systems applications. Generation of specifications, design and verification must be performed at all abstraction levels, including the system, register-transfer, logic, circuit, transistor and process levels.
This document discusses feature extraction techniques for isolated word speech recognition. It begins with an introduction to digital speech processing and speech recognition models. The main part of the document compares two common feature extraction techniques: Mel Frequency Cepstral Coefficients (MFCC) and Relative Spectral (RASTA) filtering. MFCC allows signals to extract feature vectors and provides high performance but lacks robustness. RASTA filtering reduces the impact of noise in signals and provides high robustness by band-passing feature coefficients in both log spectral and spectral domains. The document provides details on the process of MFCC feature extraction, which involves steps like framing, windowing, fast Fourier transform, mel filtering, discrete cosine transform, and calculating
International journal of signal and image processing issues vol 2015 - no 1...sophiabelthome
This document presents a study on automatic speech recognition (ASR). It discusses the different types of ASR systems including speaker-dependent, speaker-independent, and speaker-adaptive systems. It also covers the different types of utterances that can be recognized, such as isolated words, connected words, continuous speech, and spontaneous speech. The document then describes the basic phases involved in ASR, including front-end analysis using techniques like pre-emphasis, framing, windowing and feature extraction. It also discusses back-end processing using acoustic and language models to map features to words. Hidden Markov models are presented as a commonly used acoustic modeling technique in ASR systems.
Performance Calculation of Speech Synthesis Methods for Hindi languageiosrjce
The document compares the performance of two speech synthesis methods - unit selection and hidden Markov model (HMM) - for Hindi language. It finds that unit selection results in higher quality synthesized speech than HMM based on both subjective and objective quality measurements. Subjective measurements using mean opinion scores show unit selection receives higher average ratings. Objective measurements of mean square error and peak signal-to-noise ratio also indicate unit selection introduces less distortion compared to the original speech samples.
Limited Data Speaker Verification: Fusion of FeaturesIJECEIAES
The present work demonstrates experimental evaluation of speaker verification for dif- ferent speech feature extraction techniques with the constraints of limited data (less than 15 seconds). The state-of-the-art speaker verification techniques provide good performance for sufficient data (greater than 1 minutes). It is a challenging task to develop techniques which perform well for speaker verification under limited data condition. In this work different features like Mel Frequency Cepstral Coefficients (MFCC), Linear Prediction Cepstral Coefficients (LPCC), Delta (4), Delta-Delta (44), Linear Prediction Residual (LPR) and Linear Prediction Residual Phase (LPRP) are considered. The performance of individual features is studied and for better verification performance, combination of these features is attempted. A comparative study is made between Gaussian mixture model (GMM) and GMM-universal background model (GMM-UBM) through experimental evaluation. The experiments are conducted using NIST-2003 database. The experimental results show that, the combination of features provides better performance compared to the individual features. Further GMM-UBM modeling gives reduced equal error rate (EER) as compared to GMM.
A Marathi Hidden-Markov Model Based Speech Synthesis Systemiosrjce
IOSR journal of VLSI and Signal Processing (IOSRJVSP) is a double blind peer reviewed International Journal that publishes articles which contribute new results in all areas of VLSI Design & Signal Processing. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced VLSI Design & Signal Processing concepts and establishing new collaborations in these areas.
Design and realization of microelectronic systems using VLSI/ULSI technologies require close collaboration among scientists and engineers in the fields of systems architecture, logic and circuit design, chips and wafer fabrication, packaging, testing and systems applications. Generation of specifications, design and verification must be performed at all abstraction levels, including the system, register-transfer, logic, circuit, transistor and process levels
Speech to text conversion for visually impaired person using µ law compandingiosrjce
The paper represents the overall design and implementation of DSP based speech recognition and
text conversion system. Speech is usually taken as a preferred mode of operation for human being, This paper
represent voice oriented command for converting into text. We intended to compute the entire speech processing
in real time. This involves simultaneously accepting the input from the user and using software filters to analyse
the data. The comparison was then to be established by using correlation and µ law companding techniques. In
this paper, voice recognition is carried out using MATLAB. The voice command is a person independent. The
voice command is stored in the data base with the help of the function keys. The real time input speech received
is then processed in the speech recognition system where the required feature of the speech words are extracted,
filtered out and matched with the existing sample stored in the database. Then the required MATLAB processes
are done to convert the received data and into text form.
Hindi digits recognition system on speech data collected in different natural...csandit
This paper presents a baseline digits speech recognizer for Hindi language. The recording environment is different for all speakers, since the data is collected in their respective homes. The different environment refers to vehicle horn noises in some road facing rooms, internal background noises in some rooms like opening doors, silence in some rooms etc. All these recordings are used for training acoustic model. The Acoustic Model is trained on 8 speakers’ audio data. The vocabulary size of the recognizer is 10 words. HTK toolkit is used for building
acoustic model and evaluating the recognition rate of the recognizer. The efficiency of the recognizer developed on recorded data, is shown at the end of the paper and possible directions for future research work are suggested.
Approach of Syllable Based Unit Selection Text- To-Speech Synthesis System fo...iosrjce
IOSR journal of VLSI and Signal Processing (IOSRJVSP) is a double blind peer reviewed International Journal that publishes articles which contribute new results in all areas of VLSI Design & Signal Processing. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced VLSI Design & Signal Processing concepts and establishing new collaborations in these areas.Design and realization of microelectronic systems using VLSI/ULSI technologies require close collaboration among scientists and engineers in the fields of systems architecture, logic and circuit design, chips and wafer fabrication, packaging, testing and systems applications. Generation of specifications, design and verification must be performed at all abstraction levels, including the system, register-transfer, logic, circuit, transistor and process levels.
This document discusses feature extraction techniques for isolated word speech recognition. It begins with an introduction to digital speech processing and speech recognition models. The main part of the document compares two common feature extraction techniques: Mel Frequency Cepstral Coefficients (MFCC) and Relative Spectral (RASTA) filtering. MFCC allows signals to extract feature vectors and provides high performance but lacks robustness. RASTA filtering reduces the impact of noise in signals and provides high robustness by band-passing feature coefficients in both log spectral and spectral domains. The document provides details on the process of MFCC feature extraction, which involves steps like framing, windowing, fast Fourier transform, mel filtering, discrete cosine transform, and calculating
International journal of signal and image processing issues vol 2015 - no 1...sophiabelthome
This document presents a study on automatic speech recognition (ASR). It discusses the different types of ASR systems including speaker-dependent, speaker-independent, and speaker-adaptive systems. It also covers the different types of utterances that can be recognized, such as isolated words, connected words, continuous speech, and spontaneous speech. The document then describes the basic phases involved in ASR, including front-end analysis using techniques like pre-emphasis, framing, windowing and feature extraction. It also discusses back-end processing using acoustic and language models to map features to words. Hidden Markov models are presented as a commonly used acoustic modeling technique in ASR systems.
IRJET- Speech to Speech Translation SystemIRJET Journal
1. The document describes a speech-to-speech translation system that aims to facilitate conversations between people speaking different languages.
2. It discusses the architecture of the proposed system, which includes modules for speech input, speech recognition, translation, grammar correction, text-to-speech synthesis, and speech output.
3. The document also reviews related work on speech recognition, translation, and text-to-speech systems. It outlines the implementation status of the different modules in the proposed system and possibilities for future improvement, such as supporting additional languages.
IRJET- Study of Effect of PCA on Speech Emotion RecognitionIRJET Journal
This document discusses speech emotion recognition using principal component analysis (PCA). It analyzes speech features like mel frequency cepstral coefficients, pitch, energy, and formant frequency from the Berlin database containing emotions like anger, sadness, happiness, and fear. PCA is applied to reduce the feature dimension and decorrelate features. A support vector machine classifier is then used to classify emotions based on the PCA-processed features. Results show applying PCA improves the classification accuracy compared to without using PCA, with accuracy increasing from 68% to 64.5% on average.
AN ADVANCED APPROACH FOR RULE BASED ENGLISH TO BENGALI MACHINE TRANSLATIONcscpconf
This paper introduces an advanced, efficient approach for rule based English to Bengali (E2B) machine translation (MT), where Penn-Treebank parts of speech (PoS) tags, HMM (Hidden
Markov Model) Tagger is used. Fuzzy-If-Then-Rule approach is used to select the lemma from rule-based-knowledge. The proposed E2B-MT has been tested through F-Score measurement,
and the accuracy is more than eighty percent
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.
IRJET - Speech to Speech Translation using Encoder Decoder ArchitectureIRJET Journal
This document summarizes a research paper on speech-to-speech translation using an encoder-decoder architecture. It describes a system that takes speech in one language as input, recognizes the speech to generate text, translates the text to another language, and synthesizes speech in the other language as output. The system consists of three main modules: speech recognition in the source language, text translation between languages, and speech generation in the target language. It aims to enable two-way translation between spoken sentences in different languages.
Evaluation of Hidden Markov Model based Marathi Text-ToSpeech Synthesis SystemIJERA Editor
The objective of this paper is to evaluate the quality of HMM based Marathi TTS system. The main advantage of HMM technique is its ability to allow the variation in voice easily. The output speeches produced in this method have greater impact on emotion, style and intonation. The naturalness and intelligibility are the two important parameters to decide the quality of synthetic speech. Depending on the parameters specified the results of synthetic speech are categorized into 4 categories: natural speech, high quality synthetic speech, low quality synthetic speech and moderate quality synthetic speech. The results are obtained by using CT, DRT and MOS test.
Artificially Generatedof Concatenative Syllable based Text to Speech Synthesi...iosrjce
This document describes a Marathi text-to-speech (TTS) synthesis system based on a concatenative approach using syllables as the basic speech units. The system analyzes input text, performs syllabification based on linguistic rules, retrieves corresponding speech files from a corpus, concatenates the files while minimizing discontinuities at boundaries, and outputs synthesized speech. A Marathi speech corpus was created containing over 1000 sentences from various domains. Subjective quality tests found the synthesized speech to have naturalness and intelligibility comparable to natural speech. The system demonstrates an effective approach for Marathi TTS using a syllable-based concatenative method.
Efficient Speech Emotion Recognition using SVM and Decision TreesIRJET Journal
This document discusses efficient speech emotion recognition using support vector machines and decision trees. It summarizes a research paper that extracted speech features like variance, standard deviation, energy and pitch from an emotional speech corpus containing 535 speech segments expressing seven emotions. The extracted features were used to train and test an SVM classifier for emotion recognition. The classifier achieved an average accuracy of 85% across training and test sets at recognizing the seven emotions. Feature selection techniques were used to address the curse of dimensionality caused by the large number of extracted features.
IRJET- Tamil Speech to Indian Sign Language using CMUSphinx Language ModelsIRJET Journal
The document describes a proposed system to translate Tamil speech to Indian Sign Language (ISL) using speech recognition and natural language processing algorithms. It aims to help hearing-impaired people communicate independently. The system would use the CMU Sphinx speech recognition tool to convert spoken Tamil to text, then apply grammar rules and machine learning to translate the text to ISL displayed through video or animated avatars. The document reviews similar existing systems and research on speech recognition and sign language translation to inform the design and implementation of the proposed Tamil-ISL system.
Development and testing of an FPT.AI-based voicebotjournalBEEI
In recent years, voicebot has become a popular communication tool between humans and machines. In this paper, we will introduce our voicebot integrating text-to-speech (TTS) and speech-to-text (STT) modules provided by FPT.AI. This voicebot can be considered as a critical improvement of a typical chatbot because it can respond to human’s queries by both text and speech. FPT Open Speech, LibriSpeech datasets, and music files were used to test the accuracy and performance of the STT module. For the TTS module, it was tested by using text on news pages in both Vietnamese and English. To test the voicebot, Homestay Service topic questions and off-topic messages were input to the system. The TTS module achieved 100% accuracy in the Vietnamese text test and 72.66% accuracy in the English text test. In the STT module test, the accuracy for FPT open speech dataset (Vietnamese) is 90.51% and for LibriSpeech Dataset (English) is 0% while the accuracy in music files test is 0% for both. The voicebot achieved 100% accuracy in its test. Since the FPT.AI STT and TTS modules were developed to support only Vietnamese for dominating the Vietnam market, it is reasonable that the test with LibriSpeech Dataset resulted in 0% accuracy.
Natural Language Processing Theory, Applications and Difficultiesijtsrd
The promise of a powerful computing device to help people in productivity as well as in recreation can only be realized with proper human machine communication. Automatic recognition and understanding of spoken language is the first step toward natural human machine interaction. Research in this field has produced remarkable results, leading to many exciting expectations and new challenges. This field is known as Natural language Processing. In this paper the natural language generation and Natural language understanding is discussed. Difficulties in NLU, applications and comparison with structured programming language are also discussed here. Mrs. Anjali Gharat | Mrs. Helina Tandel | Mr. Ketan Bagade "Natural Language Processing Theory, Applications and Difficulties" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28092.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/28092/natural-language-processing-theory-applications-and-difficulties/mrs-anjali-gharat
This document provides an overview of speech recognition systems and recent progress in the field. It discusses different types of speech recognition including isolated word, connected word, continuous speech, and spontaneous speech. Various techniques used in speech recognition are also summarized, such as simulated evolutionary computation, artificial neural networks, fuzzy logic, Kalman filters, and Hidden Markov Models. The document reviews several papers published between 2004-2012 that studied speech recognition methods including using dynamic spectral subband centroids, Kalman filters, biomimetic computing techniques, noise estimation, and modulation filtering. It concludes that Hidden Markov Models combined with MFCC features provide good recognition results and are suitable for large vocabulary, speaker-independent, continuous speech recognition.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
IRJET - Response Analysis of Educational VideosIRJET Journal
This document summarizes a research paper that analyzes student feedback on educational videos through sentiment analysis. It proposes a system to collect student comments, preprocess the data, identify sentiment and emotions, compute student satisfaction and dissatisfaction, and visualize the results. The system uses machine learning techniques like term frequency-inverse document frequency and random forest classification. It achieved 62.5% accuracy in classifying sentiment polarity in student comments. The analysis of student responses can help teachers better understand student interest and identify areas for improvement.
IRJET- On-Screen Translator using NLP and Text DetectionIRJET Journal
This document describes a proposed on-screen text translator system using natural language processing (NLP) and text detection. The system would detect text from images or video frames using tools like OpenCV and Python-tesseract, extract the text as a string, and input it into an NLP model. The NLP model would analyze the string using techniques like LSTM and RNN to tokenize the words and return a translated output. Future work could include improving detection of curved text, integrating detection and recognition, and adding support for more languages. The goal is to provide translations of unfamiliar words directly on screen to aid reading comprehension.
The document proposes a method for building a speaker independent speech recognition system that can recognize speech in any language (tested with Hindi and Bengali) and implement it on Windows 7. It discusses using adaptive language models and hidden Markov models to map acoustic signals to words irrespective of the speaker. The implementation involves developing dictionaries with words and their corresponding phonemes, designing grammars according to language structures, and using the Sphinx speech engine alongside Java code to segment words from audio input and match them to phonemes through hidden Markov modeling. The method allows for multilingual speech recognition with improved efficiency through parallelization of processing stages.
IRJET- Text to Speech Synthesis for Hindi Language using Festival FrameworkIRJET Journal
This document describes a text-to-speech synthesis system for the Hindi language developed using the Festival framework. The system takes Hindi text as input and outputs synthesized speech. It uses a syllable-based concatenative approach where Hindi words are segmented into syllables which are then matched to recorded audio files and concatenated to generate speech. Challenges in developing text-to-speech for Hindi include accurate pronunciation rules and producing natural prosody. The system aims to improve the naturalness of synthesized Hindi speech output.
This document summarizes and compares entropy and dictionary-based techniques for lossless data compression. It discusses how entropy coding like Huffman coding assigns shorter codes to more frequent symbols, making it well-suited for JPEG images. Dictionary techniques like LZW replace strings with codes, performing better on files with repetitive data like TIFFs. While entropy coding has simpler encoding, dictionary methods have better compression ratios and decoding capability. The document also presents the proposed Huffman coding of a bitmap image to assign variable-length codes based on color probabilities.
High Quality Arabic Concatenative Speech Synthesissipij
This paper describes the implementation of TD-PSOLA tools to improve the quality of the Arabic Text-tospeech (TTS) system. This system based on Diphone concatenation with TD-PSOLA modifier synthesizer. This paper describes techniques to improve the precision of prosodic modifications in the Arabic speech synthesis using the TD-PSOLA (Time Domain Pitch Synchronous Overlap-Add) method. This approach is based on the decomposition of the signal into overlapping frames synchronized with the pitch period. The main objective is to preserve the consistency and accuracy of the pitch marks after prosodic modifications of the speech signal and diphone with vowel integrated database adjustment and optimisation.
The document describes a proposed vocal code system that allows programmers to write code using speech instead of typing. It aims to help programmers who suffer from repetitive strain injuries or other disabilities that make typing difficult. The system uses speech recognition technology to convert speech to text and then generates valid Java code based on the spoken words. It breaks the system down into modules for the graphical user interface, speech to text conversion, and code generation. It also discusses the technical approaches used, including hidden Markov models and MFCC feature extraction for speech recognition. The goal is to make programming more accessible and reduce physical strain for disabled programmers.
This document discusses a proposed speech-to-speech translation system that would allow translation between English and Hindi. It outlines the objectives of integrating speech recognition, text translation, text-to-speech synthesis, and text extraction from images into a single application. The proposed system would use neural networks like RNNs and LSTMs to perform these functions. It describes the overall architecture and flow of information between the various modules, including preprocessing text, translating with rules and word embeddings, and generating speech output. The goal is to develop a user-friendly system to help overcome language barriers.
IRJET- Speech Based Answer Sheet Evaluation SystemIRJET Journal
The document describes a proposed speech-based answer sheet evaluation system. It aims to improve on existing manual evaluation methods by utilizing speech recognition technology. The key points are:
1. The proposed system would allow examiners to provide speech input to evaluate scanned answer sheets, rather than manually entering marks. This could minimize errors and malpractices compared to existing systems.
2. Speech recognition would be implemented using Google Speech API and techniques like Hidden Markov Models and Vector Quantization. The system is intended to accurately interpret examiner speech and perform the corresponding evaluation actions.
3. By automating more of the evaluation process and providing a speech interface, the system aims to make the process easier for examiners compared to existing
IRJET- Speech to Speech Translation SystemIRJET Journal
1. The document describes a speech-to-speech translation system that aims to facilitate conversations between people speaking different languages.
2. It discusses the architecture of the proposed system, which includes modules for speech input, speech recognition, translation, grammar correction, text-to-speech synthesis, and speech output.
3. The document also reviews related work on speech recognition, translation, and text-to-speech systems. It outlines the implementation status of the different modules in the proposed system and possibilities for future improvement, such as supporting additional languages.
IRJET- Study of Effect of PCA on Speech Emotion RecognitionIRJET Journal
This document discusses speech emotion recognition using principal component analysis (PCA). It analyzes speech features like mel frequency cepstral coefficients, pitch, energy, and formant frequency from the Berlin database containing emotions like anger, sadness, happiness, and fear. PCA is applied to reduce the feature dimension and decorrelate features. A support vector machine classifier is then used to classify emotions based on the PCA-processed features. Results show applying PCA improves the classification accuracy compared to without using PCA, with accuracy increasing from 68% to 64.5% on average.
AN ADVANCED APPROACH FOR RULE BASED ENGLISH TO BENGALI MACHINE TRANSLATIONcscpconf
This paper introduces an advanced, efficient approach for rule based English to Bengali (E2B) machine translation (MT), where Penn-Treebank parts of speech (PoS) tags, HMM (Hidden
Markov Model) Tagger is used. Fuzzy-If-Then-Rule approach is used to select the lemma from rule-based-knowledge. The proposed E2B-MT has been tested through F-Score measurement,
and the accuracy is more than eighty percent
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.
IRJET - Speech to Speech Translation using Encoder Decoder ArchitectureIRJET Journal
This document summarizes a research paper on speech-to-speech translation using an encoder-decoder architecture. It describes a system that takes speech in one language as input, recognizes the speech to generate text, translates the text to another language, and synthesizes speech in the other language as output. The system consists of three main modules: speech recognition in the source language, text translation between languages, and speech generation in the target language. It aims to enable two-way translation between spoken sentences in different languages.
Evaluation of Hidden Markov Model based Marathi Text-ToSpeech Synthesis SystemIJERA Editor
The objective of this paper is to evaluate the quality of HMM based Marathi TTS system. The main advantage of HMM technique is its ability to allow the variation in voice easily. The output speeches produced in this method have greater impact on emotion, style and intonation. The naturalness and intelligibility are the two important parameters to decide the quality of synthetic speech. Depending on the parameters specified the results of synthetic speech are categorized into 4 categories: natural speech, high quality synthetic speech, low quality synthetic speech and moderate quality synthetic speech. The results are obtained by using CT, DRT and MOS test.
Artificially Generatedof Concatenative Syllable based Text to Speech Synthesi...iosrjce
This document describes a Marathi text-to-speech (TTS) synthesis system based on a concatenative approach using syllables as the basic speech units. The system analyzes input text, performs syllabification based on linguistic rules, retrieves corresponding speech files from a corpus, concatenates the files while minimizing discontinuities at boundaries, and outputs synthesized speech. A Marathi speech corpus was created containing over 1000 sentences from various domains. Subjective quality tests found the synthesized speech to have naturalness and intelligibility comparable to natural speech. The system demonstrates an effective approach for Marathi TTS using a syllable-based concatenative method.
Efficient Speech Emotion Recognition using SVM and Decision TreesIRJET Journal
This document discusses efficient speech emotion recognition using support vector machines and decision trees. It summarizes a research paper that extracted speech features like variance, standard deviation, energy and pitch from an emotional speech corpus containing 535 speech segments expressing seven emotions. The extracted features were used to train and test an SVM classifier for emotion recognition. The classifier achieved an average accuracy of 85% across training and test sets at recognizing the seven emotions. Feature selection techniques were used to address the curse of dimensionality caused by the large number of extracted features.
IRJET- Tamil Speech to Indian Sign Language using CMUSphinx Language ModelsIRJET Journal
The document describes a proposed system to translate Tamil speech to Indian Sign Language (ISL) using speech recognition and natural language processing algorithms. It aims to help hearing-impaired people communicate independently. The system would use the CMU Sphinx speech recognition tool to convert spoken Tamil to text, then apply grammar rules and machine learning to translate the text to ISL displayed through video or animated avatars. The document reviews similar existing systems and research on speech recognition and sign language translation to inform the design and implementation of the proposed Tamil-ISL system.
Development and testing of an FPT.AI-based voicebotjournalBEEI
In recent years, voicebot has become a popular communication tool between humans and machines. In this paper, we will introduce our voicebot integrating text-to-speech (TTS) and speech-to-text (STT) modules provided by FPT.AI. This voicebot can be considered as a critical improvement of a typical chatbot because it can respond to human’s queries by both text and speech. FPT Open Speech, LibriSpeech datasets, and music files were used to test the accuracy and performance of the STT module. For the TTS module, it was tested by using text on news pages in both Vietnamese and English. To test the voicebot, Homestay Service topic questions and off-topic messages were input to the system. The TTS module achieved 100% accuracy in the Vietnamese text test and 72.66% accuracy in the English text test. In the STT module test, the accuracy for FPT open speech dataset (Vietnamese) is 90.51% and for LibriSpeech Dataset (English) is 0% while the accuracy in music files test is 0% for both. The voicebot achieved 100% accuracy in its test. Since the FPT.AI STT and TTS modules were developed to support only Vietnamese for dominating the Vietnam market, it is reasonable that the test with LibriSpeech Dataset resulted in 0% accuracy.
Natural Language Processing Theory, Applications and Difficultiesijtsrd
The promise of a powerful computing device to help people in productivity as well as in recreation can only be realized with proper human machine communication. Automatic recognition and understanding of spoken language is the first step toward natural human machine interaction. Research in this field has produced remarkable results, leading to many exciting expectations and new challenges. This field is known as Natural language Processing. In this paper the natural language generation and Natural language understanding is discussed. Difficulties in NLU, applications and comparison with structured programming language are also discussed here. Mrs. Anjali Gharat | Mrs. Helina Tandel | Mr. Ketan Bagade "Natural Language Processing Theory, Applications and Difficulties" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28092.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/28092/natural-language-processing-theory-applications-and-difficulties/mrs-anjali-gharat
This document provides an overview of speech recognition systems and recent progress in the field. It discusses different types of speech recognition including isolated word, connected word, continuous speech, and spontaneous speech. Various techniques used in speech recognition are also summarized, such as simulated evolutionary computation, artificial neural networks, fuzzy logic, Kalman filters, and Hidden Markov Models. The document reviews several papers published between 2004-2012 that studied speech recognition methods including using dynamic spectral subband centroids, Kalman filters, biomimetic computing techniques, noise estimation, and modulation filtering. It concludes that Hidden Markov Models combined with MFCC features provide good recognition results and are suitable for large vocabulary, speaker-independent, continuous speech recognition.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
IRJET - Response Analysis of Educational VideosIRJET Journal
This document summarizes a research paper that analyzes student feedback on educational videos through sentiment analysis. It proposes a system to collect student comments, preprocess the data, identify sentiment and emotions, compute student satisfaction and dissatisfaction, and visualize the results. The system uses machine learning techniques like term frequency-inverse document frequency and random forest classification. It achieved 62.5% accuracy in classifying sentiment polarity in student comments. The analysis of student responses can help teachers better understand student interest and identify areas for improvement.
IRJET- On-Screen Translator using NLP and Text DetectionIRJET Journal
This document describes a proposed on-screen text translator system using natural language processing (NLP) and text detection. The system would detect text from images or video frames using tools like OpenCV and Python-tesseract, extract the text as a string, and input it into an NLP model. The NLP model would analyze the string using techniques like LSTM and RNN to tokenize the words and return a translated output. Future work could include improving detection of curved text, integrating detection and recognition, and adding support for more languages. The goal is to provide translations of unfamiliar words directly on screen to aid reading comprehension.
The document proposes a method for building a speaker independent speech recognition system that can recognize speech in any language (tested with Hindi and Bengali) and implement it on Windows 7. It discusses using adaptive language models and hidden Markov models to map acoustic signals to words irrespective of the speaker. The implementation involves developing dictionaries with words and their corresponding phonemes, designing grammars according to language structures, and using the Sphinx speech engine alongside Java code to segment words from audio input and match them to phonemes through hidden Markov modeling. The method allows for multilingual speech recognition with improved efficiency through parallelization of processing stages.
IRJET- Text to Speech Synthesis for Hindi Language using Festival FrameworkIRJET Journal
This document describes a text-to-speech synthesis system for the Hindi language developed using the Festival framework. The system takes Hindi text as input and outputs synthesized speech. It uses a syllable-based concatenative approach where Hindi words are segmented into syllables which are then matched to recorded audio files and concatenated to generate speech. Challenges in developing text-to-speech for Hindi include accurate pronunciation rules and producing natural prosody. The system aims to improve the naturalness of synthesized Hindi speech output.
This document summarizes and compares entropy and dictionary-based techniques for lossless data compression. It discusses how entropy coding like Huffman coding assigns shorter codes to more frequent symbols, making it well-suited for JPEG images. Dictionary techniques like LZW replace strings with codes, performing better on files with repetitive data like TIFFs. While entropy coding has simpler encoding, dictionary methods have better compression ratios and decoding capability. The document also presents the proposed Huffman coding of a bitmap image to assign variable-length codes based on color probabilities.
High Quality Arabic Concatenative Speech Synthesissipij
This paper describes the implementation of TD-PSOLA tools to improve the quality of the Arabic Text-tospeech (TTS) system. This system based on Diphone concatenation with TD-PSOLA modifier synthesizer. This paper describes techniques to improve the precision of prosodic modifications in the Arabic speech synthesis using the TD-PSOLA (Time Domain Pitch Synchronous Overlap-Add) method. This approach is based on the decomposition of the signal into overlapping frames synchronized with the pitch period. The main objective is to preserve the consistency and accuracy of the pitch marks after prosodic modifications of the speech signal and diphone with vowel integrated database adjustment and optimisation.
The document describes a proposed vocal code system that allows programmers to write code using speech instead of typing. It aims to help programmers who suffer from repetitive strain injuries or other disabilities that make typing difficult. The system uses speech recognition technology to convert speech to text and then generates valid Java code based on the spoken words. It breaks the system down into modules for the graphical user interface, speech to text conversion, and code generation. It also discusses the technical approaches used, including hidden Markov models and MFCC feature extraction for speech recognition. The goal is to make programming more accessible and reduce physical strain for disabled programmers.
This document discusses a proposed speech-to-speech translation system that would allow translation between English and Hindi. It outlines the objectives of integrating speech recognition, text translation, text-to-speech synthesis, and text extraction from images into a single application. The proposed system would use neural networks like RNNs and LSTMs to perform these functions. It describes the overall architecture and flow of information between the various modules, including preprocessing text, translating with rules and word embeddings, and generating speech output. The goal is to develop a user-friendly system to help overcome language barriers.
IRJET- Speech Based Answer Sheet Evaluation SystemIRJET Journal
The document describes a proposed speech-based answer sheet evaluation system. It aims to improve on existing manual evaluation methods by utilizing speech recognition technology. The key points are:
1. The proposed system would allow examiners to provide speech input to evaluate scanned answer sheets, rather than manually entering marks. This could minimize errors and malpractices compared to existing systems.
2. Speech recognition would be implemented using Google Speech API and techniques like Hidden Markov Models and Vector Quantization. The system is intended to accurately interpret examiner speech and perform the corresponding evaluation actions.
3. By automating more of the evaluation process and providing a speech interface, the system aims to make the process easier for examiners compared to existing
IRJET- Comparative Analysis of Emotion Recognition SystemIRJET Journal
This document summarizes a research paper that analyzes different machine learning models for speech emotion recognition using the SAVEE dataset. It compares CNN, RFC, XGBoost and SVM classifiers using MFCC features extracted from the audio clips. The CNN model achieved the highest accuracy for emotion recognition when using MFCC features. The paper aims to better understand human emotional states through analyzing dependencies in speech data using these machine learning techniques.
A Review On Speech Feature Techniques And Classification TechniquesNicole Heredia
This document discusses speech feature extraction and classification techniques for speech recognition systems. It provides an overview of common feature extraction methods like MFCC and LPC, and classification algorithms like ANN and SVM. MFCC mimics human auditory perception but provides weak power spectrum, while LPC is easy to calculate but does not capture information at a linear scale. ANN can learn from data but is complex for large datasets, while SVM is accurate and suitable for pattern recognition but requires fixed-length coefficients. The document evaluates these techniques and concludes that MFCC performance is more efficient than LPC for feature extraction in speech recognition.
A NEURAL MACHINE LANGUAGE TRANSLATION SYSTEM FROM GERMAN TO ENGLISHIRJET Journal
The document describes a neural machine translation system that translates from German to English. It uses a Transformer model integrated with Fuzzy Semantic Representation and Latent Topic Representation to handle rare words and capture sentence context. FSR groups rare words together and LTR uses CNN to represent sentence context as topic vectors. The model achieves improved translation performance on the WMT En-De corpus compared to baselines by handling out-of-vocabulary words and incorporating sentence level context.
Approach To Build A Marathi Text-To-Speech System Using Concatenative Synthes...IJERA Editor
Marathi is one of the oldest languages in India. This research paper describes the development of Marathi Textto-
Speech System (TTS). In Marathi TTS the input is Marathi text in Unicode. The voices are sampled from real
recorded speech. The objective of a text to speech system is to convert an arbitrary text into its corresponding
spoken waveform. Speech synthesis is a process of building machinery that can generate human-like speech
from any text input to imitate human speakers. Text processing and speech generation are two main components
of a text to speech system. To build a natural sounding speech synthesis system, it is essential that text
processing component produce an appropriate sequence of phonemic units. Generation of sequence of phonetic
units for a given standard word is referred to as letter to phoneme rule or text to phoneme rule. The
complexity of these rules and their derivation depends upon the nature of the language. The quality of a speech
synthesizer is judged by its closeness to the natural human voice and understandability. In this research paper we
described an approach to build a Marathi TTS system using concatenative synthesis method with syllable as a
basic unit of concatenation.
An Efficient Approach to Produce Source Code by Interpreting AlgorithmIRJET Journal
This document proposes a model for converting algorithms written in natural English language into source code. It aims to help programmers by allowing them to focus on logic and problem solving without worrying about syntax. The model consists of modules for basic natural language processing, interpretation, using synonyms, and personalized training. It identifies the statement type and then parses it into formal C code by recognizing trigger words and applying rules from a case frame database. The goal is to address challenges like limited natural language understanding by making the interpreter more flexible through mechanisms like synonym recognition and personalized user training. If successful, this could help both new programmers and visually impaired developers.
A survey on Enhancements in Speech RecognitionIRJET Journal
This document discusses enhancements in speech recognition and provides an overview of the history and basic model of speech recognition. It summarizes key enhancements researchers have made to improve speech recognition, especially in noisy environments. The basic model of speech recognition involves speech input, preprocessing using techniques like MFCCs, classification models like RNNs and HMMs, and output of a transcript. Researchers are working to develop robust speech recognition that can understand speech in any environment.
IRJET- Communication System for Blind, Deaf and Dumb People using Internet of...IRJET Journal
This document describes a communication system for blind, deaf, and mute people using Internet of Things technologies. The system addresses the issues of each group (blind, deaf, mute) with different techniques in a single system. It can convert images to text and speech for blind people. For deaf people, it converts speech to text. And for mute people, it converts gestures to text and speech. The system was implemented using Python and utilizes technologies like OpenCV, Tesseract OCR, and text-to-speech to enable communication across the groups. It achieved the goals of providing an independent lifestyle and a way to communicate for people with these disabilities.
This document presents a voice-based billing system that takes voice input from customers on purchased items and quantities and generates an itemized bill. It consists of three main modules: 1) A speech-to-text module that converts voice input into text using Google APIs. 2) A word tokenization module that splits the text into individual words using NLTK. 3) A bill generation module that takes the tokenized words as input to calculate the total bill amount. The system was tested on purchasing various fruits and achieved 90% accuracy compared to existing systems. It aims to reduce time complexity for billing compared to manual entry.
IRJET- Voice to Code Editor using Speech RecognitionIRJET Journal
This document presents a summary of a research paper on developing a voice-controlled code editor using speech recognition. A team of students and a professor from S.B Jain Institute of Technology, Management and Research created a Java program editor that allows users to write code using voice commands. The editor takes advantage of the natural human ability to speak language and allows coding more accurately and intuitively compared to manual typing. It analyzes the user's speech using acoustic and language modeling with Hidden Markov Models to accurately recognize commands. The proposed voice-controlled code editor is designed to reduce typing errors, improve coding speed, and enable people with disabilities to operate a computer. It will support basic editing tasks and allow switching between voice and manual input.
IRJET - Threat Prediction using Speech AnalysisIRJET Journal
This document describes a proposed system to analyze audio files and detect potential threats by performing speech recognition and sentiment analysis. The system would have three main steps: 1) Convert speech to text using machine learning algorithms like recurrent neural networks, 2) Perform sentiment analysis on the text using natural language processing techniques like naïve Bayes classification to determine if the text is positive, negative, or neutral, 3) Calculate an overall threat percentage and issue a warning if it exceeds a threshold. The goal is to automate audio surveillance and analysis to reduce time and human error compared to manual processes. Artificial neural networks would be used for both speech recognition and sentiment classification.
Modeling of Speech Synthesis of Standard Arabic Using an Expert Systemcsandit
This document describes an expert system for speech synthesis of Standard Arabic text. It involves two main stages: 1) creation of a sound database and 2) text-to-speech transformation. The transformation process involves phonetic orthographic transcription of the text and then generating voice signals corresponding to the transcribed phonetic sequence. The expert system uses a knowledge base containing sound data and rewriting rules. It transcribes text using graphemes as basic units and then concatenates sound units from the database to synthesize speech. Tests achieved a 96% success rate in pronouncing sentences correctly. Future work aims to improve prosody and develop fully automatic signal segmentation.
Real Time Direct Speech-to-Speech TranslationIRJET Journal
1. The document describes a real-time direct speech-to-speech translation system developed by students using Python and its libraries.
2. The system aims to ease communication barriers between speakers of different languages by allowing users to speak into the system and receive an immediate translation without needing text as an intermediate step.
3. The system architecture includes modules for user login, speech input, translation using Google Translate API, and output of the translation in both text and speech formats.
MULTILINGUAL SPEECH TO TEXT CONVERSION USING HUGGING FACE FOR DEAF PEOPLEIRJET Journal
The document describes a system for multilingual speech-to-text conversion using Hugging Face that aims to assist deaf individuals. The system uses a Transformer-based encoder-decoder model trained on audio datasets. Feature extraction and tokenization are performed on the audio inputs. The model is fine-tuned using Hugging Face and evaluated based on word error rate. A web application allows users to record speech via microphone and see the transcription output. The implemented model achieved a 32.42% word error rate on a Hindi language dataset. The goal is to enable seamless communication for those with hearing impairments across multiple languages.
IRJET- Voice Command Execution with Speech Recognition and SynthesizerIRJET Journal
The document describes a voice command execution system using speech recognition and text-to-speech synthesis. The proposed system allows users to complete tasks using only voice commands, reducing time delays compared to traditional systems requiring mouse/keyboard input. It recognizes three types of voice commands - social commands for question answering, web commands to access URLs, and shell commands involving file/application directories. A speech synthesizer converts text to speech to provide output to the user. The system aims to enable hands-free computing for disabled users by executing commands with only voice.
IRJET- My Buddy App: Communications between Smart Devices through Voice A...IRJET Journal
This document summarizes research on developing voice assistants that can communicate with each other without human input. It discusses artificial intelligence, natural language processing, question answering systems, and popular voice assistants like Siri, Cortana, and Amazon Alexa. The goal is to allow voice assistants to generate questions and hold conversations with each other automatically. The document provides background on AI techniques, NLP applications, question answering history, and existing voice assistants. It aims to enable voice assistants to communicate through natural language.
The document discusses a proposed customized speech recognition system that can recognize any regional language. It does this by using Microsoft SAPI to convert words in regional languages to phonemes and store them in a custom grammar database along with their associated actions. During use, a user's spoken words are converted to phonemes using SAPI and compared to the custom grammar database to identify the associated action to perform. This allows the system to recognize and respond to voice commands in any language by training itself on a user's specific regional language.
This document summarizes a research paper on developing a speech-to-text conversion system for visually impaired people using μ-law companding. The system uses MATLAB to analyze input speech signals, extract features, filter noise, and match signals to samples stored in a database to convert speech to text. A graphical user interface was created to input speech and display recognition results. The system achieved real-time speech recognition and conversion to text with high accuracy using μ-law companding techniques for signal processing and correlation comparisons to the stored samples.
Similar to IRJET- Designing and Creating Punjabi Speech Synthesis System using Hidden Markov Model (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
Accident detection system project report.pdfKamal Acharya
The Rapid growth of technology and infrastructure has made our lives easier. The
advent of technology has also increased the traffic hazards and the road accidents take place
frequently which causes huge loss of life and property because of the poor emergency facilities.
Many lives could have been saved if emergency service could get accident information and
reach in time. Our project will provide an optimum solution to this draw back. A piezo electric
sensor can be used as a crash or rollover detector of the vehicle during and after a crash. With
signals from a piezo electric sensor, a severe accident can be recognized. According to this
project when a vehicle meets with an accident immediately piezo electric sensor will detect the
signal or if a car rolls over. Then with the help of GSM module and GPS module, the location
will be sent to the emergency contact. Then after conforming the location necessary action will
be taken. If the person meets with a small accident or if there is no serious threat to anyone’s
life, then the alert message can be terminated by the driver by a switch provided in order to
avoid wasting the valuable time of the medical rescue team.
Tools & Techniques for Commissioning and Maintaining PV Systems W-Animations ...Transcat
Join us for this solutions-based webinar on the tools and techniques for commissioning and maintaining PV Systems. In this session, we'll review the process of building and maintaining a solar array, starting with installation and commissioning, then reviewing operations and maintenance of the system. This course will review insulation resistance testing, I-V curve testing, earth-bond continuity, ground resistance testing, performance tests, visual inspections, ground and arc fault testing procedures, and power quality analysis.
Fluke Solar Application Specialist Will White is presenting on this engaging topic:
Will has worked in the renewable energy industry since 2005, first as an installer for a small east coast solar integrator before adding sales, design, and project management to his skillset. In 2022, Will joined Fluke as a solar application specialist, where he supports their renewable energy testing equipment like IV-curve tracers, electrical meters, and thermal imaging cameras. Experienced in wind power, solar thermal, energy storage, and all scales of PV, Will has primarily focused on residential and small commercial systems. He is passionate about implementing high-quality, code-compliant installation techniques.
Road construction is not as easy as it seems to be, it includes various steps and it starts with its designing and
structure including the traffic volume consideration. Then base layer is done by bulldozers and levelers and after
base surface coating has to be done. For giving road a smooth surface with flexibility, Asphalt concrete is used.
Asphalt requires an aggregate sub base material layer, and then a base layer to be put into first place. Asphalt road
construction is formulated to support the heavy traffic load and climatic conditions. It is 100% recyclable and
saving non renewable natural resources.
With the advancement of technology, Asphalt technology gives assurance about the good drainage system and with
skid resistance it can be used where safety is necessary such as outsidethe schools.
The largest use of Asphalt is for making asphalt concrete for road surfaces. It is widely used in airports around the
world due to the sturdiness and ability to be repaired quickly, it is widely used for runways dedicated to aircraft
landing and taking off. Asphalt is normally stored and transported at 150’C or 300’F temperature
A high-Speed Communication System is based on the Design of a Bi-NoC Router, ...DharmaBanothu
The Network on Chip (NoC) has emerged as an effective
solution for intercommunication infrastructure within System on
Chip (SoC) designs, overcoming the limitations of traditional
methods that face significant bottlenecks. However, the complexity
of NoC design presents numerous challenges related to
performance metrics such as scalability, latency, power
consumption, and signal integrity. This project addresses the
issues within the router's memory unit and proposes an enhanced
memory structure. To achieve efficient data transfer, FIFO buffers
are implemented in distributed RAM and virtual channels for
FPGA-based NoC. The project introduces advanced FIFO-based
memory units within the NoC router, assessing their performance
in a Bi-directional NoC (Bi-NoC) configuration. The primary
objective is to reduce the router's workload while enhancing the
FIFO internal structure. To further improve data transfer speed,
a Bi-NoC with a self-configurable intercommunication channel is
suggested. Simulation and synthesis results demonstrate
guaranteed throughput, predictable latency, and equitable
network access, showing significant improvement over previous
designs
Supermarket Management System Project Report.pdfKamal Acharya
Supermarket management is a stand-alone J2EE using Eclipse Juno program.
This project contains all the necessary required information about maintaining
the supermarket billing system.
The core idea of this project to minimize the paper work and centralize the
data. Here all the communication is taken in secure manner. That is, in this
application the information will be stored in client itself. For further security the
data base is stored in the back-end oracle and so no intruders can access it.