Paper: Word Buffering Models for Improved Speech Repair Parsing

ACL ID D09-1077
Title Word Buffering Models for Improved Speech Repair Parsing
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2009
Authors
  • Tim Miller (University of Minnesota Twin Cities, Minneapolis MN)

This paper describes a time-series model for parsing transcribed speech containing disfluencies. This model differs from pre- vious parsers in its explicit modeling of a buffer of recent words, which allows it to recognize repairs more easily due to the frequent overlap in words between errors and their repairs. The parser implement- ing this model is evaluated on the stan- dard Switchboard transcribed speech pars- ing task for overall parsing accuracy and edited word detection.