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This document summarizes a seminar on voice morphing techniques. It discusses what voice morphing is, including modifying a source speaker's voice to sound like a target speaker. It then outlines the main topics that were covered in the seminar, including transform-based voice morphing systems, enhancing systems with phase prediction and spectral refinement, enabling real-time voice morphing, and conclusions about extending the techniques to other audio sounds.
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Voice morphing-101113123852-phpapp01
This document presents an overview of voice morphing technology. It discusses that voice morphing is a technique to modify a source speaker's voice to sound like a target speaker. It describes the need for voice morphing in applications like text-to-speech, public address systems, and for special effects. The technical process involves extracting spectral and pitch information from both voices and using algorithms like dynamic time warping and signal re-estimation to morph the source voice into the target voice. Some applications discussed are for altering evidence in courts or creating fake orders in military conflicts.
Voicemorphingppt 110328163403-phpapp01
Voice morphing is a technique that modifies a source speaker's speech to sound like it was spoken by a different target speaker. The process involves preprocessing the speech signal, analyzing the pitch and envelope, morphing through warping and interpolation, and re-estimating the signal. To morph voices between a male and female speaker, the pitch of the male speaker is shifted to match that of the female speaker by time-stretching the residue signal and adjusting the LPC coefficients. Potential applications include using popular speakers for public announcements, and effects in films, but limitations include difficulties in voice detection and updating systems for new languages.
Voice morphing document
Voice morphing is a technique that modifies a source speaker's speech to sound like it was spoken by a target speaker. It works by analyzing the source speech into an excitation signal and filter components, then resynthesizing it with the pitch and vocal characteristics of the target speaker. The key steps are detecting the pitches of the source and target speakers, scaling the source pitch to match the target, then resynthesizing the source speech using the target's vocal filter characteristics and the pitch-scaled excitation signal. Voice morphing was developed in 1999 and has applications in text-to-speech, dubbing, voice disguising, and public announcement systems.
Voice morphing-
It is a technique to modify a source speaker's speech to sound as if it was spoken by a target speaker.
Voice morphing enables speech patterns to be cloned
And an accurate copy of a person's voice can be made that can wishes to say, anything in the voice of someone else.
Voicemorphing
Voice morphing is a technique that modifies a source speaker's speech to sound like a target speaker. It was developed by George Papcun at Los Alamos National Laboratory. The process involves preprocessing the speech signals, analyzing pitch and formants, matching signals using dynamic time warping, and re-estimating the signals. Voice morphing can be used for text-to-speech, public address systems, and special effects. While it allows cloning speech patterns, it has limitations around normalization and requires extensive sound libraries for different languages.
Voice Morphing System for People Suffering from Laryngectomy
Voice Morphing System for People Suffering from LaryngectomyInternational Journal of Science and Research (IJSR)
This paper proposes a voice morphing system for people suffering from Laryngectomy, which is the surgical removal of all or part of the larynx or the voice box, particularly performed in cases of laryngeal cancer. A primitive method of achieving voice morphing is by extracting the source's vocal coefficients and then converting them into the target speaker's vocal parameters. In this paper, we deploy Gaussian Mixture Models (GMM) for mapping the coefficients from source to destination. However, the use of the traditional/conventional GMM-based mapping approach results in the problem of over-smoothening of the converted voice. Thus, we hereby propose a unique method to perform efficient voice morphing and conversion based on GMM, which overcomes the traditional-method effects of over-smoothening. It uses a technique of glottal waveform separation and prediction of excitations and hence the result shows that not only over-smoothening is eliminated but also the transformed vocal tract parameters match with the target. Moreover, the synthesized speech thus obtained is found to be of a sufficiently high quality. Thus, voice morphing based on a unique GMM approach has been proposed and also critically evaluated based on various subjective and objective evaluation parameters. Further, an application of voice morphing for Laryngectomees which deploys this unique approach has been recommended by this paper
Voice morphing ppt
Voice morphing is a technique that modifies a source speaker's speech to sound like a target speaker. It does this by changing the pitch from the source speaker, like a male voice, to the target speaker, like a female voice. This is done by interpolating the linear predictive coding coefficients of the source and target signals. The pitch of the morphed signal can be positioned between the source and target by varying a constant value between 0 and 1. Applications include changing voices for security or entertainment purposes, but limitations include difficulties with voice detection and requiring extensive sound libraries.
Voice morphing-101113123852-phpapp01 (1)
The document summarizes a technical seminar presentation on voice morphing. It describes voice morphing as a technique that modifies a source speaker's speech to sound like a target speaker. It discusses the need for voice morphing in applications like text-to-speech, discusses the voice morphing process which includes preprocessing, pitch and envelope analysis, morphing and signal re-estimation, and addresses limitations and advantages.
Recommended
Voice morphing-101113123852-phpapp01
This document presents an overview of voice morphing technology. It discusses that voice morphing is a technique to modify a source speaker's voice to sound like a target speaker. It describes the need for voice morphing in applications like text-to-speech, public address systems, and for special effects. The technical process involves extracting spectral and pitch information from both voices and using algorithms like dynamic time warping and signal re-estimation to morph the source voice into the target voice. Some applications discussed are for altering evidence in courts or creating fake orders in military conflicts.
Voicemorphingppt 110328163403-phpapp01
Voice morphing is a technique that modifies a source speaker's speech to sound like it was spoken by a different target speaker. The process involves preprocessing the speech signal, analyzing the pitch and envelope, morphing through warping and interpolation, and re-estimating the signal. To morph voices between a male and female speaker, the pitch of the male speaker is shifted to match that of the female speaker by time-stretching the residue signal and adjusting the LPC coefficients. Potential applications include using popular speakers for public announcements, and effects in films, but limitations include difficulties in voice detection and updating systems for new languages.
Voice morphing document
Voice morphing is a technique that modifies a source speaker's speech to sound like it was spoken by a target speaker. It works by analyzing the source speech into an excitation signal and filter components, then resynthesizing it with the pitch and vocal characteristics of the target speaker. The key steps are detecting the pitches of the source and target speakers, scaling the source pitch to match the target, then resynthesizing the source speech using the target's vocal filter characteristics and the pitch-scaled excitation signal. Voice morphing was developed in 1999 and has applications in text-to-speech, dubbing, voice disguising, and public announcement systems.
Voice morphing-
It is a technique to modify a source speaker's speech to sound as if it was spoken by a target speaker.
Voice morphing enables speech patterns to be cloned
And an accurate copy of a person's voice can be made that can wishes to say, anything in the voice of someone else.
Voicemorphing
Voice morphing is a technique that modifies a source speaker's speech to sound like a target speaker. It was developed by George Papcun at Los Alamos National Laboratory. The process involves preprocessing the speech signals, analyzing pitch and formants, matching signals using dynamic time warping, and re-estimating the signals. Voice morphing can be used for text-to-speech, public address systems, and special effects. While it allows cloning speech patterns, it has limitations around normalization and requires extensive sound libraries for different languages.
Voice Morphing System for People Suffering from Laryngectomy
Voice Morphing System for People Suffering from LaryngectomyInternational Journal of Science and Research (IJSR)
This paper proposes a voice morphing system for people suffering from Laryngectomy, which is the surgical removal of all or part of the larynx or the voice box, particularly performed in cases of laryngeal cancer. A primitive method of achieving voice morphing is by extracting the source's vocal coefficients and then converting them into the target speaker's vocal parameters. In this paper, we deploy Gaussian Mixture Models (GMM) for mapping the coefficients from source to destination. However, the use of the traditional/conventional GMM-based mapping approach results in the problem of over-smoothening of the converted voice. Thus, we hereby propose a unique method to perform efficient voice morphing and conversion based on GMM, which overcomes the traditional-method effects of over-smoothening. It uses a technique of glottal waveform separation and prediction of excitations and hence the result shows that not only over-smoothening is eliminated but also the transformed vocal tract parameters match with the target. Moreover, the synthesized speech thus obtained is found to be of a sufficiently high quality. Thus, voice morphing based on a unique GMM approach has been proposed and also critically evaluated based on various subjective and objective evaluation parameters. Further, an application of voice morphing for Laryngectomees which deploys this unique approach has been recommended by this paper
Voice morphing ppt
Voice morphing is a technique that modifies a source speaker's speech to sound like a target speaker. It does this by changing the pitch from the source speaker, like a male voice, to the target speaker, like a female voice. This is done by interpolating the linear predictive coding coefficients of the source and target signals. The pitch of the morphed signal can be positioned between the source and target by varying a constant value between 0 and 1. Applications include changing voices for security or entertainment purposes, but limitations include difficulties with voice detection and requiring extensive sound libraries.
Voice morphing-101113123852-phpapp01 (1)
The document summarizes a technical seminar presentation on voice morphing. It describes voice morphing as a technique that modifies a source speaker's speech to sound like a target speaker. It discusses the need for voice morphing in applications like text-to-speech, discusses the voice morphing process which includes preprocessing, pitch and envelope analysis, morphing and signal re-estimation, and addresses limitations and advantages.
Voice Morping ppt
Voice morphing involves transforming one speech signal into another through three main steps: 1) extracting pitch and envelope information through cepstral analysis, 2) using dynamic time warping to match pitch contours between signals and interpolating values to create intermediate morphs, and 3) re-estimating and reconstructing the morphed signal as an acoustic waveform. Applications include military psychological operations, creating fake audio evidence, and voice acting in cartoons. The document provides details on preprocessing signals, the morphing and warping process, and applications and conclusions regarding voice morphing technology.
Voice morphing
Voice morphing is a technique that modifies a source speaker's speech to sound like a target speaker. It works by preprocessing the speech signals, analyzing pitch and envelope, matching and warping the signals, and re-estimating the signal. This allows for an accurate copy of a person's voice to be made. Voice morphing has applications in text-to-speech systems, public address systems, and special effects. It can also be used to create fake conversations for use in courts or as a battlefield deception tool. The process separates speech into spectral envelope and pitch/voicing information before realigning and recombining the signals.
Voice Morphing
This document describes the process of voice morphing, which involves transitioning one speech signal into another while preserving shared characteristics. It discusses representing speech signals in a domain that separates pitch and envelope information. A key step is dynamic time warping to match pitch features between signals. The morphed signal is created through interpolation and reconverted to an acoustic waveform. Examples show morphing between different gender pairs of speakers. Voice morphing aims to smoothly transition one voice into another in a similar manner as image morphing blends two faces.
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This document discusses speech signal processing and speech recognition. It begins by defining speech processing and its relationship to digital signal processing. It then outlines several disciplines related to speech processing including signal processing, physics, pattern recognition, and computer science. The document discusses aspects of speech signals including phonemes, the speech waveform, and spectral envelope. It covers various aspects of speech processing including pre-processing, feature extraction, and recognition. It provides details on techniques for pre-processing, feature extraction including filtering, linear predictive coding, and cepstrum. Finally, it summarizes the main steps in a speech recognition procedure including endpoint detection, framing and windowing, feature extraction, and distortion measure calculations for recognition.
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- Some of the challenges in speech recognition including variations between speakers and dependence on neighboring sounds.Speech technology basics
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Voice Morping ppt
Voice morphing involves transforming one speech signal into another through three main steps: 1) extracting pitch and envelope information through cepstral analysis, 2) using dynamic time warping to match pitch contours between signals and interpolating values to create intermediate morphs, and 3) re-estimating and reconstructing the morphed signal as an acoustic waveform. Applications include military psychological operations, creating fake audio evidence, and voice acting in cartoons. The document provides details on preprocessing signals, the morphing and warping process, and applications and conclusions regarding voice morphing technology.
Voice morphing
Voice morphing is a technique that modifies a source speaker's speech to sound like a target speaker. It works by preprocessing the speech signals, analyzing pitch and envelope, matching and warping the signals, and re-estimating the signal. This allows for an accurate copy of a person's voice to be made. Voice morphing has applications in text-to-speech systems, public address systems, and special effects. It can also be used to create fake conversations for use in courts or as a battlefield deception tool. The process separates speech into spectral envelope and pitch/voicing information before realigning and recombining the signals.
Voice Morphing
This document describes the process of voice morphing, which involves transitioning one speech signal into another while preserving shared characteristics. It discusses representing speech signals in a domain that separates pitch and envelope information. A key step is dynamic time warping to match pitch features between signals. The morphed signal is created through interpolation and reconverted to an acoustic waveform. Examples show morphing between different gender pairs of speakers. Voice morphing aims to smoothly transition one voice into another in a similar manner as image morphing blends two faces.
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The document discusses speech signal processing. It begins by describing speech production, including the vocal tract model and acoustic theory of speech. It then covers various methods for speech analysis in both the time and frequency domains, including short-time analysis, short-time energy, zero crossing rate, and autocorrelation function. Parametric representations of speech such as linear predictive coding are also introduced. The document concludes by mentioning several applications of speech processing such as speech coding, recognition, and transmission over the internet.
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This document discusses speech signal processing and speech recognition. It begins by defining speech processing and its relationship to digital signal processing. It then outlines several disciplines related to speech processing including signal processing, physics, pattern recognition, and computer science. The document discusses aspects of speech signals including phonemes, the speech waveform, and spectral envelope. It covers various aspects of speech processing including pre-processing, feature extraction, and recognition. It provides details on techniques for pre-processing, feature extraction including filtering, linear predictive coding, and cepstrum. Finally, it summarizes the main steps in a speech recognition procedure including endpoint detection, framing and windowing, feature extraction, and distortion measure calculations for recognition.
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The document discusses research issues in speech processing. It covers topics like speech production, speech processing tasks, speech measurements, speech signal components, automatic speech recognition, speaker recognition, text-to-speech systems, speech coding, and a proposed speech-assisted translation corrector system. The key challenges in speech processing research are modeling the human auditory system, developing large multilingual speech databases, and generating natural sounding synthetic speech.
Homomorphic speech processing
This document discusses homomorphic speech processing and techniques for speech enhancement. It provides an overview of modeling speech production as the excitation of a linear time-invariant system. Homomorphic filtering is introduced as a way to deconvolve speech into excitation and system response using logarithmic transformations. The complex cepstrum is discussed as a representation of speech that can be used to estimate pitch, voicing and formant frequencies. Homomorphic vocoding is described as a speech coding technique that quantizes the low-time part of the cepstrum at regular intervals to encode speech. Common techniques for speech enhancement like spectral subtraction and adaptive noise cancellation are also mentioned.
Digital modeling of speech signal
This document summarizes digital modeling techniques for speech signals. It describes the vocal source and vocal tract that produce speech. It then discusses using sampling and techniques like PCM to digitally represent speech signals. Linear predictive coding is presented as a simple method to analyze speech that approximates samples as combinations of past signals. The summary concludes that linear prediction can be used for spectrum estimation by representing the vocal tract transfer function, pitch detection, and speech synthesis.
LPC for Speech Recognition
LPC is a speech compression technique that models speech production as a linear function of past speech samples. It has an analysis stage that determines filter coefficients to reproduce a block of speech from the input signal. In the decoding stage, the filter is rebuilt using the coefficients. The document analyzes cepstral coefficients of male and female voices for different Bodo vowels, finding distinctions between genders for certain frames. It concludes LPCC measures may be better for identifying a speaker's sex.
Linear Predictive Coding
Linear Predictive Coding (LPC) is one of the most powerful speech analysis techniques, and one of the most useful methods for encoding good quality speech at a low bit rate. It provides extremely accurate estimates of speech parameters, and is relatively efficient for computation.
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This document analyzes speech coding algorithms for Hindi and English languages. It discusses Linear Predictive Coding (LPC), an algorithm that accurately estimates speech parameters and represents speech signals at reduced bit rates while preserving quality. The paper proposes a voice-excited LPC algorithm and implements it on Hindi and English male and female voices. It analyzes tradeoffs between bit rates, delay, signal-to-noise ratio, and complexity. The results show low bit-rates and better signal-to-noise ratio with this algorithm.
Digital speech processing lecture1
This document provides an overview of a course on digital speech processing. The course will cover fundamentals of speech production and perception, as well as techniques for digital speech processing including short-time Fourier analysis and linear predictive coding methods. Applications that will be discussed include speech coding, synthesis, recognition, and other speech applications involving pattern matching problems. Students will learn about representations and algorithms for processing speech signals.
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This document discusses linear predictive coding (LPC) methods and horn noise detection. It begins with an introduction to speech coders and speech production modeling. It then covers the basic principles of LPC analysis, including the autocorrelation and covariance methods. It discusses solving the LPC equations and using LPC residue to detect horn noise by comparing the residue of speech, silence and known horn noise samples. The document provides results of adding speech and horn noise signals and detecting the horn noise. It concludes by listing references on speech coding algorithms, LPC, and speech processing.
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What are Linear Predictive coding, its methods, and analysis?
LPC using Autocorrelation, LPC-Vocoder, etc
An Introduction to Various Features of Speech SignalSpeech features
An overview of various temporal, spectral and cepstral features of speech signal used in digital speech processing.
For more tutorials visit:
https://sites.google.com/site/enggprojectece
An Introduction To Speech Recognition
An Introduction To Speech RecognitionDepartment of Telecommunications, Ministry of Communication & IT (INDIA)
This document provides an overview of speech recognition including:
- The topics that will be covered such as speech production, why speech recognition is difficult, and applications.
- How speech is produced through the lungs, larynx, and vocal tract and modified into different sounds.
- The main components of a speech recognition system including sound sampling, conversion to frequencies, and matching to a phoneme database.
- Some of the challenges in speech recognition including variations between speakers and dependence on neighboring sounds.Speech technology basics
Digital signal processing (DSP) involves converting analog signals to digital signals and manipulating the digital signals using software algorithms. DSP systems use analog-to-digital conversion to convert analog signals to digital signals represented as sequences of numbers. They then process the digital signals using a digital signal processor and convert them back to analog signals using digital-to-analog conversion. Key techniques in DSP include decomposing signals into simple components, processing the components individually, and then combining the results.
High Quality Arabic Concatenative Speech Synthesis
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.
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Speech Enhancement by suppressing uncorrelated acoustically added noise has been a challenging topic of research for many years. These are the primary choice for real time applications due to the simplicity and comparatively low computational load. This paper shows VAD (Voice activity detection) technique that can detect the non speech segment from the speech signal. It is also shown that it can work powerfully in an unpredictable noise ambience. The technique is mostly done in microprocessors or DSP processors because of their flexibility. But there are several advantages of FPGA over DSP processors like high cost per logic element related to these processors makes them improper for large scale use. From the experimental results, VAD method is implemented on the FPGA chip.
Speaker recognition.
This document describes how to build a simple automatic speaker recognition system. It discusses the principles of speaker recognition, which can be identification (determining which registered speaker is speaking) or verification (accepting or rejecting a speaker's claimed identity). The key components are feature extraction and feature matching. Feature extraction converts the speech waveform into features using techniques like MFCC. Feature matching then compares the extracted features to stored reference models to identify the speaker. The document focuses on the speech feature extraction process, which involves framing the speech signal, windowing frames, taking the FFT, and calculating MFCCs to characterize the signal in a way that mimics human hearing.
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Rain Technology
- 2. Contents • Introduction • What is Voice Morphing? • Transform-based voice morphing system • System Enhancement • Realtime voice morphing • Conclusion • References
- 3. Introduction Voice morphing, which is also referred to as voice transformation and voice conversion, is a technique for modifying a source speaker’s speech to sound as if it was spoken by some designated target speaker.
- 4. WHAT IS VOICE MORPHING? • Voice morphing (also known as voice transformation and voice conversion) is the software-generated alteration of a person's natural voice. • The purpose may be to add audio effects to the voice, to obscure the identity of the person or to impersonate another individual.
- 5. Transform-based voice morphing system • Overall Framework • Spectral Parameters • Linear Transforms
- 6. System Enhancement • Phase Prediction • Spectral Refinement • Tansforming Unvoiced Sounds
- 7. Real-time voice morphing • The Voice Morphing System • Voice analysis/synthesis using SMS • Phonetic recognition/alignment • Morphing
- 9. CONCLUSIONS • In this seminar, only one type of morphing has been discussed - that in which the final morph has the same duration as the longest signal. • Also we discuss the case of speech morphing in this seminar. • But the work can be extended to include audio sounds as well. • The longest signal is compressed and the morph has the same duration as the shortest signal.
- 10. REFERENCES • www.google.com • www.wikipedia.com • www.studymafia.org
- 11. Thanks
Editor's Notes
- 1