Speech Time Frequency Representations
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Speech Time-Frequency Representations
Author: Michael D. Riley
language: en
Publisher: Springer Science & Business Media
Release Date: 1989-01-31
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.
Time-Frequency Analysis
Covering a period of about 25 years, during which time-frequency has undergone significant developments, this book is principally addressed to researchers and engineers interested in non-stationary signal analysis and processing. It is written by recognized experts in the field.
Speech Spectrum Analysis
Author: Sean A. Fulop
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-05-26
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.