Digital Processing of Speech Signals
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The material in this book is intended as a one-semester course in speech processing.
The purpose of this text is to show how digital signal processing techniques
can be applied to problems related to speech communication. The book gives an
extensive description of the physical basis for speech coding including fourier
analysis, digital representation and digital and time domain models of the wave
form. It goes on to discuss homomorphic speech processing, linear predictive
coding and digital processing for machine communication by voice.
- This book is organized around several basic approaches to digital representations
of speech signals with discussions of specific parameter estimation techniques
and applications serving as examples of the utility of each representation.
Pg.___
- Chapter 2 provides a review of the fundamentals of digital signal processing
and an extensive discussion of sampling, and decimation and interpolation,
key processes that are fundamental to most speech processing systems. Pg.___
- Chapter 3 deals with digital models for the speech signal, discussing the
physical basis for sound production in the vocal tract, and discussing various
types of digital models to approximate this process. Pg.___
- Includes coverage of time domain methods in speech processing.
- Short-Time energy. Pg.___
- Average magnitude. Pg.___
- Short-Time average zero-crossing rate. Pg.___
- Short-Time autocorrelation. Pg.___
- Coverage of a variety of coders from simple pulse code modulation (PCM)
to adaptive differential PCM (ADPCM) coding, discussing the following:
- Instantaneous quantization (both uniform and nonuniform). Pg.___
- Adaptive quantization. Pg.___
- Differential quantization. Pg.___
- Predictive coding (both fixed and adaptive). Pg.___
- Each chapter contains a set of representative homework problems which are
intended to reinforce the ideas discussed in each chapter. Pg.___
Table of Contents
1. Introduction.
2. Fundamentals of Digital Speech Processing.
3. Digital Models for the Speech Signal.
4. Time-Domain Models for Speech Processing.
5. Digital Representation of the Speech Waveform.
6. Short-Time Fourier Analysis.
7. Homomorphic Speech Processing.
8. Linear Predictive Coding of Speech.
9. Digital Speech Processing for Man-Machine Communication by Voice.
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