Speech Enhancement
With the proliferation of mobile devices and hearing devices, including hearing aids and cochlear implants, there is a growing and pressing need to design algorithms that can improve speech intelligibility without sacrificing quality. Responding to this need, Speech Enhancement: Theory and Practice, Second Edition introduces readers to the basic problems of speech enhancement and the various algorithms proposed to solve these problems. Updated and expanded, this second edition of the bestselling textbook broadens its scope to include evaluation measures and enhancement algorithms aimed at improving speech intelligibility.
Fundamentals, Algorithms, Evaluation, and Future Steps
Organized into four parts, the book begins with a review of the fundamentals needed to understand and design better speech enhancement algorithms. The second part describes all the major enhancement algorithms and, because these require an estimate of the noise spectrum, also covers noise estimation algorithms. The third part of the book looks at the measures used to assess the performance, in terms of speech quality and intelligibility, of speech enhancement methods. It also evaluates and compares several of the algorithms. The fourth part presents binary mask algorithms for improving speech intelligibility under ideal conditions. In addition, it suggests steps that can be taken to realize the full potential of these algorithms under realistic conditions.
What’s New in This Edition
- Updates in every chapter
- A new chapter on objective speech intelligibility measures
- A new chapter on algorithms for improving speech intelligibility
- Real-world noise recordings (on accompanying CD)
- MATLAB® code for the implementation of intelligibility measures (on accompanying CD)
- MATLAB and C/C++ code for the implementation of algorithms to improve speech intelligibility (on accompanying CD)
Valuable Insights from a Pioneer in Speech Enhancement
Clear and concise, this book explores how human listeners compensate for acoustic noise in noisy environments. Written by a pioneer in speech enhancement and noise reduction in cochlear implants, it is an essential resource for anyone who wants to implement or incorporate the latest speech enhancement algorithms to improve the quality and intelligibility of speech degraded by noise.
Includes a CD with Code and Recordings
The accompanying CD provides MATLAB implementations of representative speech enhancement algorithms as well as speech and noise databases for the evaluation of enhancement algorithms.
Why Read This Book
You will gain a practical, algorithm-centered view of modern speech enhancement: how algorithms work, why they succeed or fail, and how to measure their impact on intelligibility and quality. The second edition updates classic methods and adds evaluation and intelligibility-focused approaches, making it a hands-on reference if you need to build or evaluate real-world speech/noise reduction systems.
Who Will Benefit
Engineers, DSP researchers, and graduate students with some signal-processing background who are designing or evaluating speech enhancement systems for hearing devices, communications, or audio applications.
Level: Intermediate — Prerequisites: Undergraduate-level signals and systems / digital signal processing, basic probability and linear algebra, and familiarity with MATLAB or Python for running examples and experiments.
Key Takeaways
- Implement common single-channel and multi-microphone enhancement algorithms (spectral subtraction, Wiener/MMSE, beamforming).
- Evaluate enhancement performance using objective metrics and understand links between objective scores and speech intelligibility.
- Apply adaptive filtering, subspace, and statistical-model methods to reduce noise while preserving speech cues.
- Design time–frequency and wavelet-based processing chains for nonstationary noise environments.
- Integrate algorithmic approaches into hearing-aid and cochlear-implant contexts and appreciate implementation constraints.
- Compare and select algorithms by trade-offs in intelligibility, quality, computational cost, and robustness.
Topics Covered
- Part I — Fundamentals: Speech, Noise, and Perception
- Time-Frequency Analysis: STFT, Spectral Analysis, and Wavelets
- Classical Single-Channel Methods: Spectral Subtraction and Wiener Filtering
- Statistical Estimators: MMSE, Ephraim-Malah, and Log-Spectral Methods
- Adaptive Filtering and Subspace Methods
- Multi-Microphone Processing and Beamforming
- Nonlinear and Masking-Based Approaches
- Evaluation: Objective Measures, Intelligibility Metrics (STOI, SII), and Subjective Testing
- Applications to Hearing Aids and Cochlear Implants
- Implementation Issues: Real-Time Constraints and Practical Considerations
- Advanced Topics: Machine-Learning Trends and Data-Driven Enhancement
- Case Studies, Reproducible Experiments, and Future Directions
Languages, Platforms & Tools
How It Compares
More application- and evaluation-focused than classic speech-processing texts like Deller/Proakis/Hansen's Discrete-Time Processing of Speech Signals, and more specialized on enhancement and intelligibility than general works such as Rabiner & Juang's Fundamentals of Speech Recognition.
