Speech Spectrum Analysis


Book Description

The accurate determination of the speech spectrum, particularly for short frames, is commonly pursued in diverse areas including speech processing, recognition, and acoustic phonetics. With this book the author makes the subject of spectrum analysis understandable to a wide audience, including those with a solid background in general signal processing and those without such background. In keeping with these goals, this is not a book that replaces or attempts to cover the material found in a general signal processing textbook. Some essential signal processing concepts are presented in the first chapter, but even there the concepts are presented in a generally understandable fashion as far as is possible. Throughout the book, the focus is on applications to speech analysis; mathematical theory is provided for completeness, but these developments are set off in boxes for the benefit of those readers with sufficient background. Other readers may proceed through the main text, where the key results and applications will be presented in general heuristic terms, and illustrated with software routines and practical "show-and-tell" discussions of the results. At some points, the book refers to and uses the implementations in the Praat speech analysis software package, which has the advantages that it is used by many scientists around the world, and it is free and open source software. At other points, special software routines have been developed and made available to complement the book, and these are provided in the Matlab programming language. If the reader has the basic Matlab package, he/she will be able to immediately implement the programs in that platform---no extra "toolboxes" are required.




Intelligent Speech Signal Processing


Book Description

Intelligent Speech Signal Processing investigates the utilization of speech analytics across several systems and real-world activities, including sharing data analytics, creating collaboration networks between several participants, and implementing video-conferencing in different application areas. Chapters focus on the latest applications of speech data analysis and management tools across different recording systems. The book emphasizes the multidisciplinary nature of the field, presenting different applications and challenges with extensive studies on the design, development and management of intelligent systems, neural networks and related machine learning techniques for speech signal processing.




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


Book Description

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.




Spectral Audio Signal Processing


Book Description

"Spectral Audio Signal Processing is the fourth book in the music signal processing series by Julius O. Smith. One can say that human hearing occurs in terms of spectral models. As a result, spectral models are especially useful in audio applications. For example, with the right spectral model, one can discard most of the information contained in a sound waveform without changing how it sounds. This is the basis of modern audio compression techniques."--Publisher's description.




Spectral Analysis of Signals


Book Description

Spectral estimation is important in many fields including astronomy, meteorology, seismology, communications, economics, speech analysis, medical imaging, radar, sonar, and underwater acoustics. Most existing spectral estimation algorithms are devised for uniformly sampled complete-data sequences. However, the spectral estimation for data sequences with missing samples is also important in many applications ranging from astronomical time series analysis to synthetic aperture radar imaging with angular diversity. For spectral estimation in the missing-data case, the challenge is how to extend the existing spectral estimation techniques to deal with these missing-data samples. Recently, nonparametric adaptive filtering based techniques have been developed successfully for various missing-data problems. Collectively, these algorithms provide a comprehensive toolset for the missing-data problem based exclusively on the nonparametric adaptive filter-bank approaches, which are robust and accurate, and can provide high resolution and low sidelobes. In this book, we present these algorithms for both one-dimensional and two-dimensional spectral estimation problems.




Advance Compression and Watermarking Technique for Speech Signals


Book Description

This book introduces methods for copyright protection and compression for speech signals. The first method introduces copyright protection of speech signal using watermarking; the second introduces compression of the speech signal using Compressive Sensing (CS). Both methods are tested and analyzed. The speech watermarking method uses technology such as Finite Ridgelet Transform (FRT), Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The performance of the method is evaluated and compared with existing watermarking methods. In the speech compression method, the standard Compressive Sensing (CS) process is used for compression of the speech signal. The performance of the proposed method is evaluated using various transform bases like Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD), and Fast Discrete Curvelet Transform (FDCuT).




Introduction to Digital Speech Processing


Book Description

Provides the reader with a practical introduction to the wide range of important concepts that comprise the field of digital speech processing. Students of speech research and researchers working in the field can use this as a reference guide.




Readings in Speech Recognition


Book Description

Speech recognition by machine : a review / D.R. Reddy -- The value of speech recognition systems / W.A. Lea -- Digital representations of speech signals / R.W. Schafer and L.R. Rabiner -- Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences / S.B. Davis and P. Mermelstein -- Vector quantization / R.M. Gray -- A joint synchrony-mean-rate model of auditory speech processing / S. Seneff -- Isolated and connected word recognition : theory and selected applications / L.R. Rabiner and S.E. Levinson -- Minimum prediction residual principle applied to speech recognition / F. Itakura -- Dynamic programming algorithm optimization for spoken word recognition / S. Hakoe and S. Chiba -- Speaker-independent recognition of isolated words using clustering techniques / L.R. Rabiner [and others]Two-level DP-matching : a dynamic programming-based pattern matching algorithm for connected word recognition / H. Sakoe -- The use of a one-stage dynamic pr ...




Techniques for Noise Robustness in Automatic Speech Recognition


Book Description

Automatic speech recognition (ASR) systems are finding increasing use in everyday life. Many of the commonplace environments where the systems are used are noisy, for example users calling up a voice search system from a busy cafeteria or a street. This can result in degraded speech recordings and adversely affect the performance of speech recognition systems. As the use of ASR systems increases, knowledge of the state-of-the-art in techniques to deal with such problems becomes critical to system and application engineers and researchers who work with or on ASR technologies. This book presents a comprehensive survey of the state-of-the-art in techniques used to improve the robustness of speech recognition systems to these degrading external influences. Key features: Reviews all the main noise robust ASR approaches, including signal separation, voice activity detection, robust feature extraction, model compensation and adaptation, missing data techniques and recognition of reverberant speech. Acts as a timely exposition of the topic in light of more widespread use in the future of ASR technology in challenging environments. Addresses robustness issues and signal degradation which are both key requirements for practitioners of ASR. Includes contributions from top ASR researchers from leading research units in the field




Computer And Network Technology - Proceedings Of The International Conference On Iccnt 2009


Book Description

ICCNT is the main annual computer and network research conference in Chennai that presents cutting edge research work. It will act as a platform for scientists, scholars, engineers and students from universities all around the world to present ongoing research and hence foster better research relations between universities and the computer and networking industry.