Broadcast news transcription using HTK

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 H 4 e v aluation data set are presented for dierent 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.