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Mathematical Foundations of Speech and Language Processing

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Cover of 'Mathematical Foundations of Speech and Language Processing'

Table of Contents

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    Book Overview
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    Chapter 1 Probability and Statistics in Computational Linguistics, a Brief Review
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    Chapter 2 Three Issues in Modern Language Modeling
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    Chapter 3 Stochastic Analysis of Structured Language Modeling
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    Chapter 4 Latent Semantic Language Modeling for Speech Recognition
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    Chapter 5 Prosody Modeling for Automatic Speech Recognition and Understanding
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    Chapter 6 Switching Dynamic System Models for Speech Articulation and Acoustics
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    Chapter 7 Segmental HMMs: Modeling Dynamics and Underlying Structure in Speech
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    Chapter 8 Modelling Graph-Based Observation Spaces for Segment-Based Speech Recognition
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    Chapter 9 Towards Robust and Adaptive Speech Recognition Models
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    Chapter 10 Graphical Models and Automatic Speech Recognition
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    Chapter 11 An Introduction to Markov Chain Monte Carlo Methods
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    Chapter 12 Semiparametric Filtering in Speech Processing
Attention for Chapter 11: An Introduction to Markov Chain Monte Carlo Methods
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