Speech Recognition: Theory and C++ Implementation
Automatic Speech Recognition (ASR) is the enabling technology for hands-free dictation and voice-triggered computer menus. It is becoming increasingly prevalent in environments such as private telephone exchanges and real-time information services. Speech Recognition introduces the principles of ASR systems, including the theory and implementation issues behind multi-speaker continuous speech recognition. Focusing on the algorithms employed in commercial and laboratory systems, the treatment enables the reader to devise practical solutions for ASR system problems. It addresses in detail C++ programming techniques used to develop ASR applications, thus offering skills that will prove useful in any large C++ based software project. Possible extensions of the well-established ASR technology are highlighted, based on "Hidden Markov Models" applied to fields such as modelling and prediction of econometric series. Features include: Accompanying website containing all C++ source code of a complete laboratory multi-speaker continuous-speech ASR system (e.g. Initialisation, Training, Recognition, Evaluation, etc.) www.wiley.com/go/becchetti-speech Detailed theoretical, mathematical and technical explanations of ASR A practical account of the functioning of ASR A crucial source of information for researchers, developers and project managers involved with ASR systems, Speech Recognition is also structured for use by students of digital signal processing, speech recognition and C++ programming techniques.
Why Read This Book
You will get a practical bridge between the signal‑processing and statistical theory behind ASR and working C++ code and design patterns for building real recognition systems. The book emphasizes algorithms used in commercial and lab systems (MFCCs, HMMs, Viterbi/Beam search, training) and shows how to structure and implement them in C++, so you can move from algorithms to a working system.
Who Will Benefit
Engineers and graduate students who build or maintain HMM‑based ASR systems and need both DSP/statistical background and concrete C++ implementation guidance.
Level: Intermediate — Prerequisites: Basic digital signal processing (sampling, filtering, FFT), probability and statistics (basic probability, expectation, likelihood), and working knowledge of C++ (classes, pointers, I/O).
Key Takeaways
- Implement standard speech front ends such as framing, windowing, preemphasis and MFCC/PLP feature extraction
- Construct and train HMM acoustic models using EM/Baum‑Welch style algorithms
- Implement Viterbi and beam‑search decoders and integrate simple n‑gram language models
- Apply speaker adaptation and practical techniques for continuous, multi‑speaker recognition
- Design and organize large C++ codebases for ASR applications with attention to modularity and performance
Topics Covered
- Introduction: overview of ASR systems and applications
- Acoustics and speech production: characteristics of speech signals
- Digital signal processing for speech: framing, windowing, pre‑emphasis, spectral analysis
- Feature extraction: MFCCs, PLP, delta features and normalization
- Statistical modeling fundamentals: probability, likelihoods, and Gaussian mixtures
- Hidden Markov Models: structure, parameterization and topology
- Training algorithms: supervised training, Baum‑Welch / EM
- Decoding and search: Viterbi algorithm, beam search and pruning strategies
- Language modeling: n‑gram models and integration with decoders
- Speaker adaptation and robustness techniques
- System architecture: components, data flow and I/O
- C++ implementation techniques: class design, memory/performance considerations and testing
- Practical examples and case studies; performance evaluation
- Appendices: mathematical derivations and code excerpts
Languages, Platforms & Tools
How It Compares
More hands‑on and implementation‑oriented than Rabiner & Juang's 'Fundamentals of Speech Recognition' (which is more theoretical); complements general NLP/LM coverage in Jurafsky & Martin by focusing on acoustic modeling and C++ system design.
