Geoffrey Zweig

EECS Department, University of California, Berkeley

Technical Report No. UCB/CSD-96-927

, 1996

http://www2.eecs.berkeley.edu/Pubs/TechRpts/1996/CSD-96-927.pdf

This report describes a method for structuring dynamic Bayesian networks so that word and sentence-level models can be constructed from low-level phonetic models. This ability is a fundamental prerequisite for large-scale speech recognition systems, and is well-addressed in the context of hidden Markov models. With dynamic Bayesian networks, however, subword units cannot simply be concatenated together, and an entirely different approach is necessary.

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BibTeX citation:

@techreport{Zweig:CSD-96-927,
    Author= {Zweig, Geoffrey},
    Title= {Dynamic Bayesian Networks and the Concatenation Problem in Speech Recognition},
    Year= {1996},
    Month= {Dec},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/1996/5297.html},
    Number= {UCB/CSD-96-927},
    Abstract= {This report describes a method for structuring dynamic Bayesian networks so that word and sentence-level models can be constructed from low-level phonetic models. This ability is a fundamental prerequisite for large-scale speech recognition systems, and is well-addressed in the context of hidden Markov models. With dynamic Bayesian networks, however, subword units cannot simply be concatenated together, and an entirely different approach is necessary.},
}

EndNote citation:

%0 Report
%A Zweig, Geoffrey 
%T Dynamic Bayesian Networks and the Concatenation Problem in Speech Recognition
%I EECS Department, University of California, Berkeley
%D 1996
%@ UCB/CSD-96-927
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/1996/5297.html
%F Zweig:CSD-96-927