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Phase-based Speech Processing

Author: Parham Aarabi

Publisher: World Scientific

Published: 2006

Total Pages: 153

ISBN-13: 9812566120

This is the first book that takes a detailed look at the importance of phase in the design of speech processing systems. Phase, in comparison with amplitude, is often ignored for speech recognition applications. Thus, this book highlights some of the important ways in which the phase of speech signals can be utilized for sound localization, enhancement, and recognition.This book also discusses the state-of-the-art research in phase-based speech processing, starting from the basics of signal processing and recording, to single microphone speech recognition, the recognition of speech and the processing of speech by humans, as well as the importance of phase in human speech recognition and multi-microphone phase-based speech processing.

Phase-based Speech Processing

Author: Parham Aarabi

Publisher:

Published: 2005

Total Pages: 153

ISBN-13: 9789812775023

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Single Channel Phase-Aware Signal Processing in Speech Communication

Author: Pejman Mowlaee

Publisher: John Wiley & Sons

Published: 2016-12-27

Total Pages: 253

ISBN-13: 1119238811

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An overview on the challenging new topic of phase-aware signal processing Speech communication technology is a key factor in human-machine interaction, digital hearing aids, mobile telephony, and automatic speech/speaker recognition. With the proliferation of these applications, there is a growing requirement for advanced methodologies that can push the limits of the conventional solutions relying on processing the signal magnitude spectrum. Single-Channel Phase-Aware Signal Processing in Speech Communication provides a comprehensive guide to phase signal processing and reviews the history of phase importance in the literature, basic problems in phase processing, fundamentals of phase estimation together with several applications to demonstrate the usefulness of phase processing. Key features: Analysis of recent advances demonstrating the positive impact of phase-based processing in pushing the limits of conventional methods. Offers unique coverage of the historical context, fundamentals of phase processing and provides several examples in speech communication. Provides a detailed review of many references and discusses the existing signal processing techniques required to deal with phase information in different applications involved with speech. The book supplies various examples and MATLAB® implementations delivered within the PhaseLab toolbox. Single-Channel Phase-Aware Signal Processing in Speech Communication is a valuable single-source for students, non-expert DSP engineers, academics and graduate students.

Intelligent Speech Signal Processing

Author: Nilanjan Dey

Publisher: Academic Press

Published: 2019-06-15

Total Pages: 210

ISBN-13: 0128181303

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Intelligent Speech Signal Processing investigates the utilization of speech analytics across several systems and real-world activities, including sharing data analytics related information, creating collaboration networks between several participants, and implementing video-conferencing in different application areas. It provides a forum for readers to discover the characteristics of intelligent speech signal processing systems across different domains. Chapters focus on the latest applications of speech data analysis and management tools across different recording systems. The book emphasizes the multi-disciplinary nature of the field, presenting different applications and challenges with extensive studies on the design, implementation, development, and management of intelligent systems, neural networks, and related machine learning techniques for speech signal processing. Highlights different data analytics techniques in speech signal processing, including machine learning, and data mining Illustrates different applications and challenges across the design, implementation, and management of intelligent systems and neural networks techniques for speech signal processing Includes coverage of biomodal speech recognition, voice activity detection, spoken language and speech disorder identification, automatic speech to speech summarization, and convolutional neural networks

Robust Speech Recognition of Uncertain or Missing Data

Author: Dorothea Kolossa

Publisher: Springer Science & Business Media

Published: 2011-07-14

Total Pages: 387

ISBN-13: 3642213170

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Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition. The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models.

New Spectral Methods for Analysis of Source/filter Characteristics of Speech Signals

Author: Baris Bozkurt

Publisher: Presses univ. de Louvain

Published: 2006

Total Pages: 125

ISBN-13: 2874630136

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This study proposes a new spectral representation called the Zeros of Z-Transform (ZZT), which is an all-zero representation of the z-transform of the signal. In addition, new chirp group delay processing techniques are developed for analysis of resonances of a signal. The combination of the ZZT representation with the chirp group delay processing algorithms provides a useful domain to study resonance characteristics of source and filter components of speech. Using the two representations, effective algorithms are developed for: source-tract decomposition of speech, glottal flow parameter estimation, formant tracking and feature extraction for speech recognition. The ZZT representation is mainly important for theoretical studies. Studying the ZZT of a signal is essential to be able to develop effective chirp group delay processing methods. Therefore, first the ZZT representation of the source-filter model of speech is studied for providing a theoretical background. We confirm through ZZT representation that anti-causality of the glottal flow signal introduces mixed-phase characteristics in speech signals. The ZZT of windowed speech signals is also studied since windowing cannot be avoided in practical signal processing algorithms and the effect of windowing on ZZT representation is drastic. We show that separate patterns exist in ZZT representations of windowed speech signals for the glottal flow and the vocal tract contributions. A decomposition method for source-tract separation is developed based on these patterns in ZZT. We define chirp group delay as group delay calculated on a circle other than the unit circle in z-plane. The need to compute group delay on a circle other than the unit circle comes from the fact that group delay spectra are often very noisy and cannot be easily processed for formant tracking purposes (the reasons are explained through ZZT representation). In this thesis, we propose methods to avoid such problems by modifying the ZZT of a signal and further computing the chirp group delay spectrum. New algorithms based on processing of the chirp group delay spectrum are developed for formant tracking and feature estimation for speech recognition. The proposed algorithms are compared to state-of-the-art techniques. Equivalent or higher efficiency is obtained for all proposed algorithms. The theoretical parts of the thesis further discuss a mixed-phase model for speech and phase processing problems in detail. Index Terms—spectral representation, source-filter separation, glottal flow estimation, formant tracking, zeros of z-transform, group delay processing, phase processing.

Phase-based Speech Processing

Author: Guangji Shi

Publisher:

Published: 2006

Total Pages: 282

ISBN-13: 9780494157954

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The performance of automatic speech recognition (ASR) systems degrades significantly in adverse environments due to ambient noise and reverberation. This problem becomes even greater in hands-free speech applications, where the microphones can be placed far away from the speaker of interest. Environmental robustness has become a major barrier that prevents ASR from a wide range of applications such as voice recognition in a car and voice controlled hand-held devices. In this research, the importance of phase in robust speech recognition is explored. First, the effect of phase uncertainty on the recognition accuracy of human listeners is investigated. The goal is to get a quantitative measure on the importance of phase. The results show that the importance of phase varies with SNR (signal-to-noise ratio). At low SNR conditions, phase can have a significant impact on speech recognition accuracy. Next, motivated by the importance of phase in multi-microphone signal processing, a phase-based dual-microphone noise masking approach is proposed for speech enhancement. By utilizing the time delay of the speech source of interest to the two microphones and the actual phases of the signals recorded by both microphones, the algorithm filters the noise signal in the short-time Fourier transform domain. By doing so, the noise components are distorted beyond recognition and the speech recognition accuracy is improved. The effectiveness of this approach is demonstrated through performance comparison with alternative techniques. Lastly, an automatic parameter estimation technique is developed to further optimize its performance. The parameter of the phase-based dual-microphone filter is adjusted in run-time automatically by performing likelihood calculations of the enhanced speech features using a prior speech model. Speech recognition tests show that this adaptive approach not only achieves better recognition accuracy, but also improves the filter's robustness when time delay estimates are inaccurate.

Progress in Nonlinear Speech Processing

Author: Yannis Stylianou

Publisher: Springer Science & Business Media

Published: 2007-03-30

Total Pages: 280

ISBN-13: 3540715037

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This book constitutes of the major results of the EU COST (European Cooperation in the field of Scientific and Technical Research) Action 277: NSP, Nonlinear Speech Processing, running from April 2001 to June 2005. Coverage includes such areas as speech analysis for speech synthesis, speech recognition, speech-non speech discrimination and voice quality assessment, speech enhancement, and emotional state detection.

Advances in Non-Linear Modeling for Speech Processing

Author: Raghunath S. Holambe

Publisher: Springer Science & Business Media

Published: 2012-02-21

Total Pages: 109

ISBN-13: 1461415055

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Advances in Non-Linear Modeling for Speech Processing includes advanced topics in non-linear estimation and modeling techniques along with their applications to speaker recognition. Non-linear aeroacoustic modeling approach is used to estimate the important fine-structure speech events, which are not revealed by the short time Fourier transform (STFT). This aeroacostic modeling approach provides the impetus for the high resolution Teager energy operator (TEO). This operator is characterized by a time resolution that can track rapid signal energy changes within a glottal cycle. The cepstral features like linear prediction cepstral coefficients (LPCC) and mel frequency cepstral coefficients (MFCC) are computed from the magnitude spectrum of the speech frame and the phase spectra is neglected. To overcome the problem of neglecting the phase spectra, the speech production system can be represented as an amplitude modulation-frequency modulation (AM-FM) model. To demodulate the speech signal, to estimation the amplitude envelope and instantaneous frequency components, the energy separation algorithm (ESA) and the Hilbert transform demodulation (HTD) algorithm are discussed. Different features derived using above non-linear modeling techniques are used to develop a speaker identification system. Finally, it is shown that, the fusion of speech production and speech perception mechanisms can lead to a robust feature set.

Advances in Nonlinear Speech Processing

Author: Mohamed Chetouani

Publisher: Springer

Published: 2007-12-06

Total Pages: 293

ISBN-13: 3540773479

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This intriguing book constitutes the thoroughly refereed postproceedings of the International Conference on Non-Linear Speech Processing, NOLISP 2007, held in Paris, France, in May 2007. The 24 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on nonlinear and non-conventional techniques, speech synthesis, speaker recognition, speech recognition, and many other subjects.