|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
RECENT ADVANCES IN BROADCAST NEWS TRANSCRIPTION
D.Y. Kim, G. Evermann, T. Hain, D. Mrva, S.E. Tranter, L. Wang & P.C. Woodland
This paper describes recent advances in the CU-HTK Broadcast News English (BN-E) transcription system and its performance in the DARPA/NIST Rich Transcription 2003 Speech-to-Text (RT-03) evaluation.
Heteroscedastic linear discriminant analysis (HLDA) and discriminative training, which were previously developed in the context of the recognition of conversational telephone speech, have been successfully applied to the BN-E task for the first time. A number of new features have also been added. These include gender-dependent (GD) discriminative training; and modified discriminative training using lattice re-generation and combination.
On the 2003 evaluation set the system gave an overall word error rate of 10.7% in less than 10 times real time (10xRT).
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