Speech and Audio Processing: A MATLAB®-based Approach
With this comprehensive and accessible introduction to the field, you will gain all the skills and knowledge needed to work with current and future audio, speech, and hearing processing technologies. Topics covered include mobile telephony, human-computer interfacing through speech, medical applications of speech and hearing technology, electronic music, audio compression and reproduction, big data audio systems and the analysis of sounds in the environment. All of this is supported by numerous practical illustrations, exercises, and hands-on MATLAB® examples on topics as diverse as psychoacoustics (including some auditory illusions), voice changers, speech compression, signal analysis and visualisation, stereo processing, low-frequency ultrasonic scanning, and machine learning techniques for big data. With its pragmatic and application driven focus, and concise explanations, this is an essential resource for anyone who wants to rapidly gain a practical understanding of speech and audio processing and technology.
Why Read This Book
You will get a practical, MATLAB-driven introduction to modern speech and audio engineering that balances theory with hands-on examples and exercises. The book shows you how to apply DSP algorithms, spectral analysis, perceptual models and machine-learning techniques to real problems from mobile telephony to audio compression and environmental sound analysis.
Who Will Benefit
Engineers and graduate students with some DSP background who want an applied, example-rich guide to speech, audio and hearing technologies and MATLAB implementations.
Level: Intermediate — Prerequisites: Undergraduate-level signals and systems (discrete-time concepts), basic calculus and linear algebra, introductory probability and statistics, and familiarity with MATLAB programming.
Key Takeaways
- Implement common DSP building blocks in MATLAB, including FFT-based analysis, windowing, and digital filters
- Analyze and design speech and audio processing chains for tasks such as compression, enhancement and playback
- Design and apply perceptual and psychoacoustic models to improve audio coding and evaluation
- Develop adaptive filtering and noise-reduction algorithms for speech enhancement in realistic environments
- Apply spectral, wavelet and time–frequency techniques for feature extraction and classification in audio and speech tasks
Topics Covered
- 1. Introduction to Speech and Audio Processing
- 2. Signals, Sampling and Basic Digital Signal Processing
- 3. Spectral Analysis and the FFT
- 4. Digital Filter Design and Implementation
- 5. Time–Frequency Methods and Wavelets
- 6. Speech Production, Perception and Psychoacoustics
- 7. Speech Coding and Audio Compression
- 8. Noise Reduction and Adaptive Filtering
- 9. Feature Extraction and Machine Learning for Audio
- 10. Applications: Mobile Telephony, Hearing Technology and Electronic Music
- 11. Audio Analysis in the Environment and Big‑Data Considerations
- 12. Practical MATLAB Examples, Exercises and Project Suggestions
Languages, Platforms & Tools
How It Compares
More applied and MATLAB-focused than Gold & Morgan's Speech and Audio Signal Processing, and less mathematically intensive than Quatieri's Discrete-Time Speech Signal Processing — ideal if you want hands-on examples over formal proofs.
