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.
REF proposed a TAG-based noisy channel model for disfluency detection.
A TAG-Based Noisy-Channel Model Of Speech Repairs
Annual Meeting Of The Association For Computational Linguistics
Computer Science