WordNet-based semantic relatedness measures in automatic speech recognition for meetings

Authors:
Michael Pucher
Affiliations:
Telecommunications Research Center Vienna, Vienna, Austria
Venue:
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Year:
2007

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Abstract

This paper presents the application of WordNet-based semantic relatedness measures to Automatic Speech Recognition (ASR) in multi-party meetings. Different word-utterance context relatedness measures and utterance-coherence measures are defined and applied to the rescoring of N-best lists. No significant improvements in terms of Word-Error-Rate (WER) are achieved compared to a large word-based n-gram baseline model. We discuss our results and the relation to other work that achieved an improvement with such models for simpler tasks.