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"This thesis presents an extensive study of the short time spectrum analysis-synthesis of speech. This type of speech processing attempts to synthesize speech without the short time Fourier transform phase information. Several existing analysis-synthesis methods are presented. In addition, five other methods are attempted experimentally. The results of these experiments are explained, identifying some very important properties of the short time spectrum analysis-synthesis. One of the methods was shown to synthesize a high fidelity speech. Finally, a comparison is made between this method and other known methods which are based on short time Fourier transform approach."--Abstract.
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.
The first edition of this book has enjoyed a gratifying existence. 1s sued in 1965, it found its intended place as a research reference and as a graduate-Ievel text. Research laboratories and universities reported broad use. Published reviews-some twenty-five in number-were universally kind. Subsequently the book was translated and published in Russian (Svyaz; Moscow, 1968) and Spanish (Gredos, S.A.; Madrid, 1972). Copies of the first edition have been exhausted for several years, but demand for the material continues. At the behest of the publisher, and with the encouragement of numerous colleagues, a second edition was begun in 1970. The aim was to retain the original format, but to expand the content, especially in the areas of digital communications and com puter techniques for speech signal processing. As before, the intended audience is the graduate-Ievel engineer and physicist, but the psycho physicist, phonetician, speech scientist and linguist should find material of interest.
"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.
Essential principles, practical examples, current applications, and leading-edge research. In this book, Thomas F. Quatieri presents the field's most intensive, up-to-date tutorial and reference on discrete-time speech signal processing. Building on his MIT graduate course, he introduces key principles, essential applications, and state-of-the-art research, and he identifies limitations that point the way to new research opportunities. Quatieri provides an excellent balance of theory and application, beginning with a complete framework for understanding discrete-time speech signal processing. Along the way, he presents important advances never before covered in a speech signal processing text book, including sinusoidal speech processing, advanced time-frequency analysis, and nonlinear aeroacoustic speech production modeling. Coverage includes: Speech production and speech perception: a dual view Crucial distinctions between stochastic and deterministic problems Pole-zero speech models Homomorphic signal processing Short-time Fourier transform analysis/synthesis Filter-bank and wavelet analysis/synthesis Nonlinear measurement and modeling techniques The book's in-depth applications coverage includes speech coding, enhancement, and modification; speaker recognition; noise reduction; signal restoration; dynamic range compression, and more. Principles of Discrete-Time Speech Processing also contains an exceptionally complete series of examples and Matlab exercises, all carefully integrated into the book's coverage of theory and applications.
This is an introduction and brief overview of the techniques and algorithms used in the design of speech systems. The author focuses on signal processing, and briefly describes the roles of other disciplines such as electronics, computing science, linguistics and physiology.
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.
1.1. Steps in the initial auditory processing. 4 2 THE TIME-FREQUENCY ENERGY REPRESENTATION 2.1. Short-time spectrum of a steady-state Iii. 9 2.2. Smoothed short-time spectra. 9 2.3. Short-time spectra of linear chirps. 13 2.4. Short-time spectra of /w /'s. 15 2.5. Wide band spectrograms of /w /'s. 16 Spectrograms of rapid formant motion. 2.6. 17 2.7. Wigner distribution and spectrogram. 21 2.8. Wigner distribution and spectrogram of cos wot. 23 2.9. Concentration ellipses for transform kernels. 28 2.10. Concentration ellipses for complementary kernels. 42 42 2.11. Directional transforms for a linear chirp. 47 2.12. Spectrograms of /wioi/ with different window sizes. 2.13. Wigner distribution of /wioi/. 49 2.14. Time-frequency autocorrelation function of /wioi/. 49 2.15. Gaussian transform of Iwioi/. 50 2.16. Directional transforms of lwioi/. 52 3 TIME-FREQUENCY FILTERING 3.1. Recovering the transfer function by filtering. 57 3.2. Estimating 'aliased' transfer function. 61 3.3. T-F autocorrelation function of an impulse train. 70 3.4. T-F autocorrelation function of LTI filter output. 70 Windowing recovers transfer function. 3.5. 72 3.6. Shearing the time-frequency autocorrelation function. 75 3.7. T-F autocorrelation function for FM filter. 76 3.8. T-F autocorrelation function of FM filter output. 77 3.9. Windowing recovers transfer function. 79 4 THE SCHEMATIC SPECTROGRAM Problems with pole-fitting approach.
Forty-three reprinted papers.