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Discriminative training of hierarchical acoustic models for large vocabulary continuous speech recognition.
Content Provider | CiteSeerX |
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Author | Chang, Hung-An Glass, James R. |
Abstract | In this paper we propose discriminative training of hierarchical acoustic models for large vocabulary continuous speech recognition tasks. After presenting our hierarchical modeling framework, we describe how the models can be generated with either Minimum Classification Error or large-margin training. Experiments on a large vocabulary lecture transcription task show that the hierarchical model can yield more than 1.0 % absolute word error rate reduction over non-hierarchical models for both kinds of discriminative training. Index Terms — hierarchical acoustic modeling, discriminative training, LVCSR 1. |
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Access Restriction | Open |
Content Type | Text |
Resource Type | Article |