Advances in transcription of broadcast news and conversational telephone speech within the combined EARS BBN/LIMSI system

  • Authors:

  • S. Matsoukas;J. -L. Gauvain;G. Adda;T. Colthurst;Chia-Lin Kao;O. Kimball;L. Lamel;F. Lefevre;J. Z. Ma;J. Makhoul;L. Nguyen;R. Prasad;R. Schwartz;H. Schwenk;Bing Xiang

  • Affiliations:

  • BBN Technol., Cambridge, MA;-;-;-;-;-;-;-;-;-;-;-;-;-;-

  • Venue:
  • IEEE Transactions on Audio, Speech, and Language Processing
  • Year:
  • 2006

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Abstract

This paper describes the progress made in the transcription of broadcast news (BN) and conversational telephone speech (CTS) within the combined BBN/LIMSI system from May 2002 to September 2004. During that period, BBN and LIMSI collaborated in an effort to produce significant reductions in the word error rate (WER), as directed by the aggressive goals of the Effective, Affordable, Reusable, Speech-to-text [Defense Advanced Research Projects Agency (DARPA) EARS] program. The paper focuses on general modeling techniques that led to recognition accuracy improvements, as well as engineering approaches that enabled efficient use of large amounts of training data and fast decoding architectures. Special attention is given on efforts to integrate components of the BBN and LIMSI systems, discussing the tradeoff between speed and accuracy for various system combination strategies. Results on the EARS progress test sets show that the combined BBN/LIMSI system achieved relative reductions of 47% and 51% on the BN and CTS domains, respectively