Discrete-Time Processing of Speech Signals (IEEE Press Classic Reissue)
Commercial applications of speech processing and recognition are fast becoming a growth industry that will shape the next decade. Now students and practicing engineers of signal processing can find in a single volume the fundamentals essential to understanding this rapidly developing field. IEEE Press is pleased to publish a classic reissue of Discrete--Time Processing of Speech Signals. Specially featured in this reissue is the addition of valuable World Wide Web links to the latest speech data references. This landmark book offers a balanced discussion of both the mathematical theory of digital speech signal processing and critical contemporary applications. The authors provide a comprehensive view of all major modern speech processing areas: speech production physiology and modeling, signal analysis techniques, coding, enhancement, quality assessment, and recognition. You will learn the principles needed to understand advanced technologies in speech processing ---- from speech coding for communications systems to biomedical applications of speech analysis and recognition. Ideal for self--study or as a course text, this far--reaching reference book offers an extensive historical context for concepts under discussion, end--of--chapter problems, and practical algorithms. Discrete--Time Processing of Speech Signals is the definitive resource for students, engineers, and scientists in the speech processing field. An Instructora s Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley Makerting Department.
Why Read This Book
You should read this book if you want a thorough, DSP-centered treatment of speech problems that links signal-processing theory to practical speech analysis, coding and early recognition techniques. It gives you worked explanations of LPC, cepstral methods, pitch detection, and other building blocks you’ll use in real speech systems.
Who Will Benefit
Intermediate-level engineers and graduate students working on speech/audio signal processing, speech coding, or feature extraction for recognition systems.
Level: Intermediate — Prerequisites: Basic signals & systems, Fourier analysis, and familiarity with discrete-time signal processing; some exposure to probability and linear algebra helps.
Key Takeaways
- Explain speech production models and map them to discrete-time signal models used in analysis and synthesis.
- Apply linear predictive coding (LPC) and Levinson-Durbin methods to estimate vocal-tract parameters and synthesize speech.
- Compute and interpret cepstral and spectral representations for feature extraction and formant analysis.
- Implement robust pitch (fundamental frequency) estimation and voicing detection methods.
- Describe common speech coding techniques and the trade-offs between bitrate, quality, and algorithmic complexity.
- Use practical analysis workflows (windowing, spectrograms, filterbanks) for speech measurement and preprocessing.
Topics Covered
- 1. Introduction to Speech Signal Processing
- 2. Speech Production and Acoustic Theory
- 3. Discrete-Time Models of Speech
- 4. Time-Domain Analysis and Short-Time Methods
- 5. Spectral and Cepstral Analysis
- 6. Linear Predictive Coding (LPC) and Inverse Filtering
- 7. Pitch Detection and Voicing
- 8. Speech Coding and Compression Techniques
- 9. Speech Recognition Fundamentals and Feature Extraction
- 10. Speech Synthesis and Vocoders
- 11. Noise Reduction and Speech Enhancement (practical considerations)
- 12. Filter banks, Multirate Methods and Time-Frequency Representations
- 13. Practical Issues, Data Sets and Implementation Notes
Languages, Platforms & Tools
How It Compares
Covers much of the DSP-focused material found in Rabiner & Schafer's classic texts but is more discrete-time/DSP oriented and more practical than the heavy statistical-recognition emphasis in Rabiner & Juang's "Fundamentals of Speech Recognition."
