Broadcast news transcription using HTK

Author

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

Author_Institution

Dept. of Eng., Cambridge Univ., UK

Volume

2

fYear

1997

fDate

21-24 Apr 1997

Firstpage

719

Abstract

This paper examines the issues in extending a large vocabulary speech recognition system designed for clean and noisy read speech tasks to handle broadcast news transcription. Results using the 1995 DARPA H4 evaluation data set are presented for different front-end analyses and 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 over previous HTK large vocabulary systems including decoder-guided segmentation, segment clustering, cache-based language modelling, and combined MAP and MLLR adaptation. The system runs in multiple passes through the data and the detailed results of each pass are given

Keywords

maximum likelihood estimation; radio broadcasting; speech recognition; television broadcasting; 1995 DARPA H4 evaluation data set; 1996 H4 evaluation; HTK system; broadcast news transcription; cache-based language modelling; combined MAP-MLLR adaptation; decoder-guided segmentation; front-end analyses; large vocabulary speech recognition system; maximum a priori estimation; maximum likelihood linear regression; segment clustering; unsupervised model adaptation; Background noise; Bandwidth; Broadcasting; Hidden Markov models; Maximum likelihood linear regression; Microphones; Robustness; Speech enhancement; Speech recognition; Vocabulary;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on

Conference_Location

Munich

ISSN

1520-6149

Print_ISBN

0-8186-7919-0

Type

conf

DOI

10.1109/ICASSP.1997.596005

Filename

596005