A TAG-based noisy channel model of speech repairs

  • Authors:
  • Mark Johnson;Eugene Charniak

  • Affiliations:
  • Brown University, Providence, RI;Brown University, Providence, RI

  • Venue:
  • ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper describes a noisy channel model of speech repairs, which can identify and correct repairs in speech transcripts. A syntactic parser is used as the source model, and a novel type of TAG-based transducer is the channel model. The use of TAG is motivated by the intuition that the reparandum is a "rough copy" of the repair. The model is trained and tested on the Switchboard disfluency-annotated corpus.