Abstract for woodland_darpa97

Proc. DARPA Speech Recognition Workshop '97, pp. 73-78


P.C. Woodland, M.J.F. Gales, D. Pye & S.J. Young

April 1997

This paper describes our efforts in extending a large vocabulary speech recognition system to handle broadcast news transcription. Results using the 1995 DARPA H4 evaluation data set are presented for different front-end analyses and for the use of unsupervised model adaptation using maximum likelihood linear regression (MLLR). The HTK system for the 1996 H4 evaluation is then described. It includes a number of new features compared to previous HTK large vocabulary systems including decoder-guided segmentation, segment clustering, cache-based language modelling, and combined MAP and MLLR adaptation. The system makes multiple passes through the data and the detailed results of each pass are given. The overall word error rate obtained by the 1996 evaluation system was 27.5%, and a bug-fixed version reduced this to 26.6%.

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