Digital Processing of Speech Signals
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.
Why Read This Book
You should read this book if you want a rigorous, DSP-first grounding in how speech is represented, analyzed, and coded: it connects classical Fourier and digital signal processing techniques to practical speech problems. You will gain a clear understanding of homomorphic (cepstral) methods and linear prediction that still underpin modern speech and audio systems.
Who Will Benefit
Graduate students, DSP engineers, and researchers who need a solid theoretical and algorithmic foundation in speech signal analysis, coding, and modeling.
Level: Intermediate — Prerequisites: Basic signals & systems, discrete-time Fourier transform, and elementary probability; familiarity with basic digital filtering and linear algebra is helpful.
Key Takeaways
- Describe the physical and source-filter models of speech production and relate them to DSP representations.
- Apply Fourier and short-time spectral analysis techniques to characterize speech signals.
- Use homomorphic processing and cepstral analysis to separate source and filter characteristics and perform pitch/formant estimation.
- Derive and implement linear predictive coding (LPC) analyses and understand LPC-based vocoding and residual coding.
- Design and evaluate basic speech coding schemes and spectral parameterization methods for communication applications.
Topics Covered
- Introduction and overview of speech processing
- Acoustic theory of speech production and source–filter model
- Digital representation and sampling of speech
- Fourier analysis and short-time spectral methods for speech
- Spectral estimation and practical windowing considerations
- Homomorphic (cepstral) methods and deconvolution
- Linear predictive analysis: theory and algorithms
- LPC implementation, inverse filtering, and formant estimation
- Residual analysis, pitch detection, and voicing
- Speech coding and vocoders based on LPC
- Applications to machine communication and recognition
- Appendices: mathematical tools and practical considerations
Languages, Platforms & Tools
How It Compares
This classic is more foundational and DSP-focused than modern texts like Gold & Morgan's 'Speech and Audio Signal Processing' (more application-oriented) and Quatieri's 'Discrete-Time Speech Signal Processing' (more modern, broader coverage of algorithms and implementation).
