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 methods.- Semiparametric filtering in speech processing.- List of workshop participants.
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From the reviews: "The topics covered are mostly related to acoustic and language modeling for automatic speech recognition (ASR). … I found the book very interesting. … I would recommend it only to readers who are already familiar with statistical methods for language processing. I think that Mathematical Foundations of Speech and Language Processing is, nevertheless, a good reference about recent trends in the fields of ASR and language processing, which are indeed very relevant to current research in MT." (M. Federico, Machine Translation, Vol. 20, 2006)
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