Ebook: Mathematical Foundations of Speech and Language Processing
- Tags: Applications of Mathematics, Language Translation and Linguistics, Pattern Recognition, Information and Communication Circuits
- Series: The IMA Volumes in Mathematics and its Applications 138
- Year: 2004
- Publisher: Springer-Verlag New York
- Edition: 1
- Language: English
- pdf
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.
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.
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.
Content:
Front Matter....Pages i-x
Probability and Statistics in Computational Linguistics, a Brief Review....Pages 1-26
Three Issues in Modern Language Modeling....Pages 27-36
Stochastic Analysis of Structured Language Modeling....Pages 37-71
Latent Semantic Language Modeling for Speech Recognition....Pages 73-103
Prosody Modeling for Automatic Speech Recognition and Understanding....Pages 105-114
Switching Dynamic System Models for Speech Articulation and Acoustics....Pages 115-133
Segmental HMMs: Modeling Dynamics and Underlying Structure in Speech....Pages 135-156
Modelling Graph-Based Observation Spaces for Segment-Based Speech Recognition....Pages 157-167
Towards Robust and Adaptive Speech Recognition Models....Pages 169-189
Graphical Models and Automatic Speech Recognition....Pages 191-245
An Introduction to Markov Chain Monte Carlo Methods....Pages 247-270
Semiparametric Filtering in Speech Processing....Pages 271-281
Back Matter....Pages 283-289
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.
Content:
Front Matter....Pages i-x
Probability and Statistics in Computational Linguistics, a Brief Review....Pages 1-26
Three Issues in Modern Language Modeling....Pages 27-36
Stochastic Analysis of Structured Language Modeling....Pages 37-71
Latent Semantic Language Modeling for Speech Recognition....Pages 73-103
Prosody Modeling for Automatic Speech Recognition and Understanding....Pages 105-114
Switching Dynamic System Models for Speech Articulation and Acoustics....Pages 115-133
Segmental HMMs: Modeling Dynamics and Underlying Structure in Speech....Pages 135-156
Modelling Graph-Based Observation Spaces for Segment-Based Speech Recognition....Pages 157-167
Towards Robust and Adaptive Speech Recognition Models....Pages 169-189
Graphical Models and Automatic Speech Recognition....Pages 191-245
An Introduction to Markov Chain Monte Carlo Methods....Pages 247-270
Semiparametric Filtering in Speech Processing....Pages 271-281
Back Matter....Pages 283-289
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