Search Contact information
University of Cambridge Home Department of Engineering
University of Cambridge > Engineering Department > Machine Intelligence Lab

Abstract for kim_asru2003

Proc. IEEE ASRU2003


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).

| (ftp:) | (http:) | (ftp:) kim_asru2003.pdf | (http:) kim_asru2003.pdf |

If you have difficulty viewing files that end '.gz', which are gzip compressed, then you may be able to find tools to uncompress them at the gzip web site.

If you have difficulty viewing files that are in PostScript, (ending '.ps' or '.ps.gz'), then you may be able to find tools to view them at the gsview web site.

We have attempted to provide automatically generated PDF copies of documents for which only PostScript versions have previously been available. These are clearly marked in the database - due to the nature of the automatic conversion process, they are likely to be badly aliased when viewed at default resolution on screen by acroread.

© 2005 Cambridge University Engineering Dept
Information provided by milab-maintainer