Principles of Experimental Phonetics

By Norman J. Lass | Go to book overview

Chapter 11
Speech Recognition
by Computer
Jared Bernstein, Horacio Franco Chapter Outline
Introduction
Current Applications
Future Applications
Technical Overview
Functional Description and Relation to Speech Synthesis
Internal Structure of Hidden Markov Model Speech Recognition
Potential Intermediate Representations
Task Types
History from 1970 to 1990
Performance Specification
Recognition System Design
Signal Analysis
Searching the Compiled Language Model
The Compiled Language Model
The Search
Methods and Materials for Training
Vector Codebook Selection
Acoustic Model Training
Characteristics of HMM Training for Continuous Speech
Evaluation
Applications
Commercial
Educational
Components of Foreign Language Competence
Live Instruction
Language Education
Pronunciation Scoring
Alignment
Training Prosodic and Segmental Scorers
Authoring Lessons and Tests
Future Research
Missing Resources
Missing Science
Fast Speaker Adaptation
Source Separation
Noise Immunity
Language Modeling
Detail Acuity
Summary
Key Terms
adaptation 414
analog signal 416
continuous speech 423
delta spectrum 419
digital signal 416
discrete Fourier transform 417
error rate 414
finite state machine 411
frame 420
hidden Markov model 411
Markov model 419
perplexity 414
speaker adaptation 431
speaker dependent system 413

-408-

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