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2007

WordNet-based Semantic Relatedness Measures in Automatic Speech Recognition for Meetings

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WordNet-based Semantic Relatedness Measures in Automatic Speech Recognition for Meetings
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 Nbest lists. No significant improvements in terms of Word-Error-Rate (WER) are achieved compared to a large word-based ngram baseline model. We discuss our results and the relation to other work that achieved an improvement with such models for simpler tasks.
Michael Pucher
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where ACL
Authors Michael Pucher
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