Minimum Bayes Risk Estimation and Decoding in Large Vocabulary Continuous Speech Recognition
نویسندگان
چکیده
منابع مشابه
Minimum Bayes Risk Estimation and Decoding in Large Vocabulary Continuous Speech Recognition
Minimum risk estimation and decoding strategies based on lattice segmentation techniques can be used to refine large vocabulary continuous speech recognition systems through the estimation of the parameters of the underlying hidden Mark models and through the identification of smaller recognition tasks which provides the opportunity to incorporate novel modeling and decoding procedures in LVCSR...
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Lattice segmentation techniques developed for Minimum Bayes Risk decoding in large vocabulary speech recognition tasks are used to compute the statistics needed for discriminative training algorithms that estimate HMM parameters so as to reduce the overall risk over the training data. New estimation procedures are developed and evaluated for both small and large vocabulary recognition tasks, an...
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Iterative estimation procedures that minimize empirical risk based on general loss functions such as the Levenshtein distance have been derived as extensions of the Extended Baum Welch algorithm. While reducing expected loss on training data is a desirable training criterion, these algorithms can be difficult to apply. They are unlike MMI estimation in that they require an explicit listing of t...
متن کاملHypothesis spaces for minimum Bayes risk training in large vocabulary speech recognition
The Minimum Bayes Risk (MBR) framework has been a successful strategy for the training of hidden Markov models for large vocabulary speech recognition. Practical implementations of MBR must select an appropriate hypothesis space and loss function. The set of word sequences and a word-based Levenshtein distance may be assumed to be the optimal choice but use of phoneme-based criteria appears to ...
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ژورنال
عنوان ژورنال: IEICE Transactions on Information and Systems
سال: 2006
ISSN: 0916-8532,1745-1361
DOI: 10.1093/ietisy/e89-d.3.900