Sinossi
Speech Pattern Processing.- 1. The State-of-the-Art in Speech.- 2. Speech Patterning.- 3. Speech Pattern Processing.- 4. Whither a Unified Theory?.- 4.1 Towards a Theory.- 4.2 Practical Issues.- 5. What We Know.- 6. Some Things We Don't Know.- 7. The Way Forward.- References.- Psycho-acoustics and Speech Perception.- 1. Introduction.- 2. Psycho-acoustics.- 3. Speech Perception.- 3.1 Vowel Reduction and Schwa.- 3.2 Spectro-temporal Dynamics of Formant Transitions.- 3.3 Consonant Reduction.- 4. Discussion.- References.- Acoustic Modelling for Large Vocabulary Continuous Speech Recognition.- 1. Introduction.- 2. Overview of LVCSR Architecture.- 3. Front End Processing.- 4. Basic Phone Modelling.- 4.1 HMM Phone Models.- 4.2 HMM Parameter Estimation.- 4.3 Context-Dependent Phone Models.- 5. Adaptation for LVCSR.- 5.1 Maximum Likelihood Linear Regression.- 5.2 Estimating the MLLR Transforms.- 6. Progress in LVCSR.- 7. Discriminative Training for LVCSR.- 8. Conclusions.- References.- Tree-based Dependence Models for Speech Recognition.- 1. Introduction.- 2. Hidden Tree Framework.- 3. Hidden Dependence Trees.- 3.1 The Mathematical Framework.- 3.2 Application to Speech.- 3.3 Topology Design and Parameter Estimation.- 3.4 Experiments.- 4. Multiscale Tree Processes.- 4.1 The Mathematical Framework.- 4.2 Application to Speech.- 4.3 Topology Design and Parameter Estimation.- 4.4 Experiments.- 5. Discussion.- References.- Connectionist and Hybrid Models for Automatic Speech Recognition.- 1. Introduction.- 2. A Brief Overview of Neural Networks.- 2.1 Basic Principles.- 2.2 Main Models for ASR.- 3. Signal Processing and Feature Extraction using ANNs.- 4. Neural Networks as Static Pattern Classifiers.- 4.1 Speech Pattern Classification with Perceptrons.- 4.2 Feature Maps.- 5. Dynamic Aspects.- 5.1 Position of the Problem.- 5.2 Time Delays.- 5.3 Dynamic Classifiers.- 5.4 Recurrent NNs.- 6. Hybrid Models.- 6.1 Position of the Problem.- 6.2 Proposed Solutions.- 7. Conclusion.- References.- Computational Models for Auditory Speech Processing.- 1. Introduction.- 2. A nonlinear computational model for basilar membrane wave motions.- 3. Frequency-domain and time-domain computational solutions to the BM model.- 4. Interval analysis of auditory model's outputs for temporal information extraction.- 5. IPIH representation of clean and noisy speech sounds.- 6. Speech recognition experiments.- 7. Summary and discussions.- References.- Speaker Adaptation of CDHMMs Using Bayesian Learning.- 1. Introduction.- 2. Bayesian Estimation of CDHMMs.- 2.1 Prior Density Definition.- 2.2 Forgetting Mechanism.- 2.3 Prior Parameter Estimation and MAP Solution.- 3. Acoustic Normalization.- 4. Tasks, Corpus and System.- 5. Speaker Adaptation Experiments.- 6. Conclusions.- References.- Discriminative Improvement of the Representation Space for Continuous Speech Recognition.- 1. Introduction.- 2. Discriminative Feature Extraction.- 3. SGDFE Algorithm for CSR.- 4. Experimental Results.- 5. Conclusions.- References.- Dealing with Loss of Synchronism in Multi-Band Continuous Speech Recognition Systems.- 1. Introduction.- 2. Forcing Synchronism Between the Bands.- 2.1 First Approach.- 2.2 Experiments.- 3. Modeling Loss of Synchronism.- 3.1 Theoretical Approach.- 3.2 Experimental Approach.- 4. Conclusion.- References.- K-Nearest Neighbours Estimator in a HMM-Based Recognition System.- 1. Introduction.- 2. K-NN Assessment.- 3. K-NN estimator in HMM.- 3.1 Adaptation Principle.- 3.2 HMM Estimation Improvement.- 4. Evaluations.- 4.1 Recognition rates.- 4.2 SNALC Evaluation.- 5. Perspectives.- References.- Robust Speech Recognition.- 1. Mismatches between Training and Testing.- 1.1 Speech Variation.- 1.2 Inter-Speaker Variation.- 2. Reducing Mismatches to Improve Speech Recognition.- 2.1 Principles of Adaptive Speech Recognition.- 2.2 Three Principal Adaptation Methods for Reducing Mismatches.- 2.3 Important Practical Issues.- 2.4 N-Best-Based Unsupervised Adaptation.- 3. Conclusion
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
