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I Foundations
1 Introduction
2 Theory and Practice of Support Vector Machines Optimization
3 From Binary Classification to Categorial Prediction
II Acoustic Modeling
4 A Large Margin Algorithm for Forced Alignment
5 A Kernel Wrapper for Phoneme Sequence Recognition
6 Augmented Statistical Models: Using Dynamic Kernels for Acoustic Models
7 Large Margin Training of Continuous Density Hidden Markov Models
III Language Modeling
8 A Survey of Discriminative Language Modeling Approaches for Large Vocabulary Continuous Speech Recognition
9 Large Margin Methods for Part-of-Speech Tagging
10 A Proposal for a Kernel Based Algorithm for Large Vocabulary Continuous Speech Recognition
IV Applications
11 Discriminative Keyword Spotting
12 Kernel-based Text-independent Speaker Verification
13 Spectral Clustering for Speech Separation
Automatic Speech and Speaker Recognition
Large Margin and Kernel Methods
Joseph Keshet
Samy Bengio
Large Margin and Kernel Methods
Joseph Keshet
Samy Bengio
Table of Contents
1 Introduction
2 Theory and Practice of Support Vector Machines Optimization
3 From Binary Classification to Categorial Prediction
II Acoustic Modeling
4 A Large Margin Algorithm for Forced Alignment
5 A Kernel Wrapper for Phoneme Sequence Recognition
6 Augmented Statistical Models: Using Dynamic Kernels for Acoustic Models
7 Large Margin Training of Continuous Density Hidden Markov Models
III Language Modeling
8 A Survey of Discriminative Language Modeling Approaches for Large Vocabulary Continuous Speech Recognition
9 Large Margin Methods for Part-of-Speech Tagging
10 A Proposal for a Kernel Based Algorithm for Large Vocabulary Continuous Speech Recognition
IV Applications
11 Discriminative Keyword Spotting
12 Kernel-based Text-independent Speaker Verification
13 Spectral Clustering for Speech Separation
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