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Speech Recognition and Understanding

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Cover of 'Speech Recognition and Understanding'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Hidden Markov Models for Speech Recognition — Strengths and Limitations
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    Chapter 2 Hidden Markov Models and Speaker Adaptation
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    Chapter 3 A 20,000 word automatic speech recognizer
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    Chapter 4 Automatic adjustments of the Markov models topology for speech recognition applications over the telephone
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    Chapter 5 Phonetic Structure Inference of Phonemic HMM
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    Chapter 6 Phonetic Units and Phonotactical Structure Inference by Ergodic Hidden Markov Models
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    Chapter 7 Clustering of Gaussian densities in hidden Markov models
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    Chapter 8 Developments in High-Performance Connected Digit Recognition
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    Chapter 9 Robust Speaker-Independent Hidden Markov Model Based Word Spotter
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    Chapter 10 Robust Speech Recognition in Noisy and Reverberant Environments
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    Chapter 11 An ISDN speech server based on speaker independent continuous Hidden Markov Models
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    Chapter 12 RAMSES: A Spanish Demisyllable Based Continuous Speech Recognition System
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    Chapter 13 Speaker Independent 1000 Words Speech Recognition in Spanish
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    Chapter 14 Continuously Variable Transition Probability HMM for Speech Recognition
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    Chapter 15 Context-Dependent Phonetic Hidden Markov Models for Speaker-Independent Continuous Speech Recognition
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    Chapter 16 Speaker Independent Continuous Speech Recognition Using Continuous Density Hidden Markov Models
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    Chapter 17 A Fast Lexical Selection Strategy for Large Vocabulary Continuous Speech Recognition
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    Chapter 18 Performance of a Speaker-Independent Continuous Speech Recognizer
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    Chapter 19 Automatic Transformation of Speech Databases for Continuous Speech Recognition
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    Chapter 20 Iterative Optimization of the Data Driven Analysis in Continuous Speech
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    Chapter 21 Syllable-based stochastic models for continuous speech recognition
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    Chapter 22 Word Hypothesization in Continuous Speech Recognition
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    Chapter 23 Phone Recognition Using High Order Phonotactic Constraints
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    Chapter 24 An Efficient Structure for Continuous Speech Recognition
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    Chapter 25 Search Organization for Large Vocabulary Continuous Speech Recognition
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    Chapter 26 Neural Networks or Hidden Markov Models for Automatic Speech Recognition: Is there a Choice?
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    Chapter 27 Neural Networks for Continuous Speech Recognition
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    Chapter 28 Connectionist Large Vocabulary Speech Recognition
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    Chapter 29 The cortical column as a model for speech recognition: principles and first experiments
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    Chapter 30 Radial Basis Functions for Speech Recognition
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    Chapter 31 Phonetic features extraction using Time-Delay Neural Networks
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    Chapter 32 Improved Broad Phonetic Classification and Segmentation with an Auditory Model
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    Chapter 33 Automatic Learning of a Production Rule System for Acoustic-Phonetic Decoding
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    Chapter 34 Stochastic Grammars and Pattern Recognition
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    Chapter 35 Basic Methods of Probabilistic Context Free Grammars
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    Chapter 36 A Probabilistic Approach to Person-Robot Dialogue
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    Chapter 37 Experimenting Text Creation by Natural-Language, Large-Vocabulary Speech Recognition
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    Chapter 38 DUALGRAM: An Efficient Method for Representing Limited-Domain Language Models
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    Chapter 39 Strategies for Speech Recognition and Understanding using Layered Protocols
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    Chapter 40 TINA: A Probabilistic Syntactic Parser for Speech Understanding Systems
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    Chapter 41 The Voyager Speech Understanding System: A Progress Report
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    Chapter 42 The Interaction of Word Recognition and Linguistic Processing in Speech Understanding
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    Chapter 43 Linguistic Processing in a Speech Understanding System
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    Chapter 44 Linguistic Tools for Speech Recognition and Understanding
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    Chapter 45 Evidential reasoning and the combination of knowledge and statistical techniques in syllable based speech recognition
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    Chapter 46 Data Base Management for Use with Acoustic-Phonetic Speech Data Bases
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    Chapter 47 BPF Outputs Compared with Formant Frequencies and LPC’s for the Recognition of Vowels
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    Chapter 48 A Codification of Error Signal by Splines Functions
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    Chapter 49 Specific Distance for Feature Selection in Speech Recognition
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    Chapter 50 Multiple Template Modeling of Sublexical Units
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    Chapter 51 Learning Structural Models of Sublexical Units
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    Chapter 52 On the use of Negative Samples in the MGGI Methodology and its application for Difficult Vocabulary Recognition Tasks
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    Chapter 53 A New Method for Dynamic Time Alignment of Speech Waveforms
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    Chapter 54 A New Technique for Automatic Segmentation of Continuous Speech
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    Chapter 55 Segmentation of speech based upon a linear model of the effects of coarticulation
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Title
Speech Recognition and Understanding
Published by
Springer, Berlin, Heidelberg, December 2012
DOI 10.1007/978-3-642-76626-8
ISBNs
978-3-64-276628-2, 978-3-64-276626-8
Editors

Pietro Laface, Renato De Mori