语音语言处理导论

　　导读
　　Acknowledgements and copyright notices
　　1 Introduction
　　 1.1 About this book
　　 1.2 Purpose of this book
　　 1.3 Some reasons to use this book
　　 1.4 What's in the book (and what's not)
　　 1.5 Computational set-up needed for this book
　　 1.6 Computational skills that are necessary in order to use the book
　　 1.7 Free software suggestions
　　 1.8 Book structure
　　2 Sounds and numbers
　　 2.1 Preparatory assignments
　　 2.2 Solutions
　　 2.3 Sampling
　　 2.4 Quantization
　　 2.5 The sampling theorem
　　 2.6 Generating a signal
　　 2.7 Numeric data types
　　 2.8 The program
　　 2.9 Structure of a loop
　　 2.10 Structure of an array
　　 2.11 Calculating the cosine values
　　 2.12 Structure of the program
　　 2.13 Writing the signal to a file
　　 Chapter summary
　　 Further Exercises
　　 Further reading
　　3 Digital filters and resonators
　　 3.1 Operations on sequences of numbers
　　 3.2 A program for calculating RMS amplitude
　　 3.3 Filtering
　　 3.4 A program for calculating running means of 4
　　 3.5 Smoothing over a longer time-window
　　 3.6 Avoiding the need for long window
　　 3.7 IIR filters in C
　　 3.8 Structure of the Klatt formant synthesizer
　　 Chapter summary
　　 Exercises
　　 Further reading
　　4 Frequency analysis and linear predictive coding
　　 4.1 Spectral analysis
　　 4.2 Spectral analysis in C
　　 4.3 Cepstral analysis
　　 4.4 Computation of the cepstrum in C
　　 4.5 Pitch tracking using cepstral analysis
　　 4.6 Voicing detection
　　 4.7 f0estimation by the autocorrelation method
　　 4.8 Linear predictive coding
　　 4.9 C programs for LPC analysis and resynthesis
　　 4.10 Trying it out
　　 4.11 Applications of LPC
　　 Chapter Summary
　　 Further exercises
　　 Further reading
　　5 Finite-state machines
　　 5. 1 Some simple examples
　　 5.2 A more serious example
　　 5.3 Deterministic and non-deterministic automata
　　 5.4 Implementation in Prolog
　　 5.5 Prolog's processing strategy and the treatment of variables
　　 5.6 Generating strings
　　 5.7 Three possibly useful applications o{ that idea
　　 5.8 Another approach to describing finite-state machines
　　 5.9 Self-loops
　　 5.10 Finite-state transducers(FSTs)
　　 5.11 Using finite-state transducers to relate speech to phonemes
　　 5.12 Finite-state phonology
　　 5.13 Finite-state syntactic processing
　　 Chapter summary
　　 Further exercises
　　 Further reading
　　6 Introduction to speech recognition techniques
　　 6.1 Architectures for speech recognition
　　 6.2 The pattern-recognition approach
　　 6.3 Dynamic time warping
　　 6.4 Applications
　　 6.5 Sources of variability in speech
　　 Chapter summary
　　 Further reading
　　7 Probabilistic finite-state models
　　 7.1 Introduction
　　 7.2 Indeterminacy: n-gram models for part-of-speech tagging
　　 7.3 Some probability theory for language modelling
　　 7.4 Markov models
　　 7.5 Trigram models
　　 7.6 Incompleteness of the training corpus
　　 7.7 Part-of-speech model calculations
　　 7.8 Using HMMs for speech recognition
　　 7.9 Chomsky's objections to Markov models and some rejoinders
　　 Chapter summary
　　 Further reading
　　8 Parsing
　　 8.1 Introduction
　　 8.9 A demo
　　 8.3 Intuitive parsing
　　 8.4 Recursive descent parsing
　　 8.5 The simplest parsing program
　　 8.6 Difference lists
　　 8.7 Generating a parse tree
　　 8.8 Syllabification
　　 8.9 Other parsing algorithms
　　 8.10 Chart parsing
　　 8.11 Depth-first vs. breadth-first search
　　 8.19 Deterministic parsing, Marcus parsing and minimal commitment parsing
　　 8.13 Parallel parsing
　　 Chapter summary
　　 Further reading
　　9 Using probabilistie grammars
　　 9.1 Motivations
　　 9.2 Probabilistic context-free grammars
　　 9.3 Estimation of rule probabilities
　　 9.4 A practical example
　　 9.5 A limitation of probabilistic context-free grammars
　　 9.6 Tree adjoining grammars
　　 9.7 Data-oriented parsing
　　 Chapter Summary
　　 Conclusion and suggestions for further reading
　　Appendix:The American Standard Code for
　　Information Interchange (ASCII)
　　Glossary
　　References
　　Index