Mathematical Foundations of Speech and Language Processing

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December 25, 2021 | History

Mathematical Foundations of Speech and Language Processing

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Speech and language technologies continue to grow in importance as they are used to create natural and efficient interfaces between people and machines, and to automatically transcribe, extract, analyze, and route information from high-volume streams of spoken and written information. The workshops on Mathematical Foundations of Speech Processing and Natural Language Modeling were held in the Fall of 2000 at the University of Minnesota's NSF-sponsored Institute for Mathematics and Its Applications, as part of a "Mathematics in Multimedia" year-long program. Each workshop brought together researchers in the respective technologies on one hand, and mathematicians and statisticians on the other hand, for an intensive week of cross-fertilization. There is a long history of benefit from introducing mathematical techniques and ideas to speech and language technologies. Examples include the source-channel paradigm, hidden Markov models, decision trees, exponential models and formal languages theory. It is likely that new mathematical techniques, or novel applications of existing techniques, will once again prove pivotal for moving the field forward. This volume consists of original contributions presented by participants during the two workshops. Topics include language modeling, prosody, acoustic-phonetic modeling, and statistical methodology.

Publish Date
Publisher
Springer New York
Language
English
Pages
289

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Edition Availability
Cover of: Mathematical Foundations of Speech and Language Processing
Mathematical Foundations of Speech and Language Processing
2004, Springer New York
electronic resource / in English

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Book Details


Table of Contents

Probability and statistics in computational linguistics, a brief review
Three issues in modern language modeling
Stochastic analysis of Structured Language Modeling
Latent semantic language modeling for speech recognition
Prosody modeling for automatic speech recognition and understanding
Switching dynamic system models for speech articulation and acoustics
Segmental HMMS: Modeling dynamics and underlying structure in speech
Modelling graph-based observation spaces for segment-based speech recognition
Towards robust and adaptive speech recognition models
Graphical models and automatic speech recognition
An introduction to Markov chain Monte Carlo method
Semiparametric filtering in speech processing.

Edition Notes

Online full text is restricted to subscribers.

Also available in print.

Mode of access: World Wide Web.

Published in
New York, NY
Series
The IMA Volumes in Mathematics and its Applications -- 138, IMA volumes in mathematics and its applications -- 138.

Classifications

Dewey Decimal Class
519
Library of Congress
T57-57.97, TA1-2040

The Physical Object

Format
[electronic resource] /
Pagination
1 online resource (x, 289 pages).
Number of pages
289

ID Numbers

Open Library
OL27073217M
Internet Archive
mathematicalfoun00gema
ISBN 10
1461264847, 1441990178
ISBN 13
9781461264842, 9781441990174
OCLC/WorldCat
853270315

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Download catalog record: RDF / JSON / OPDS | Wikipedia citation
December 25, 2021 Edited by ImportBot import existing book
December 25, 2021 Edited by ImportBot import existing book
July 5, 2019 Created by MARC Bot Imported from Internet Archive item record