The AMI meeting transcription system: progress and performance

Authors:
Thomas Hain;Lukas Burget;John Dines;Giulia Garau;Martin Karafiat;Mike Lincoln;Jithendra Vepa;Vincent Wan
Affiliations:
Department of Computer Science, University of Sheffield, Sheffield, UK;Faculty of Information Engineering, Brno University of Technology, Brno, Czech Republic;IDIAP Research Institute, Martigny, Switzerland;Centre for Speech Technology Research, University of Edinburgh, Edinburgh, UK;Faculty of Information Engineering, Brno University of Technology, Brno, Czech Republic;Centre for Speech Technology Research, University of Edinburgh, Edinburgh, UK;IDIAP Research Institute, Martigny, Switzerland;Department of Computer Science, University of Sheffield, Sheffield, UK
Venue:
MLMI'06 Proceedings of the Third international conference on Machine Learning for Multimodal Interaction
Year:
2006

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Abstract

We present the AMI 2006 system for the transcription of speech in meetings. The system was jointly developed by multiple sites on the basis of the 2005 system for participation in the NIST RT'05 evaluations. The paper describes major developments such as improvements in automatic segmentation, cross-domain model adaptation, inclusion of MLP based features, improvements in decoding, language modelling and vocal tract length normalisation, the use of a new decoder, and a new system architecture. This is followed by a comprehensive description of the final system and its performance in the NIST RT'06s evaluations. In comparison to the previous year word error rate results on the individual headset microphone task were reduced by 20% relative.