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Vocabulary optimization based on perplexity
1997 IEEE International Conference on Acoustics, Speech, and Signal Processing
In this paper, we suggest a method to optimize the vocabulary for a given task using the perplexity criterion. The optimization allows us to reduce the size of the vocabulary at the same perplexity of the original word based vocabulary or to reduce perplexity at the same vocabulary size. This new approach is an alternative to phoneme n-gram language model in the speech recognition search stage. We show the convergence of our approach on the Korean training corpus. This method may provide an
doi:10.1109/icassp.1997.596214
dblp:conf/icassp/Hwang97
fatcat:or3xet2p2fesfnzbjm4i5zdxtm