TY  - BOOK
AB  - We present STIR (STrongly Incremental Repair detection), a system that detects speech repairs and edit terms on transcripts incrementally with minimal latency. STIR uses information-theoretic measures from n-gram models as its principal decision features in a pipeline of classifiers detecting the different stages of repairs. Results on the Switchboard disfluency tagged corpus show utterance-final accuracy on a par with state-of-the-art incremental repair detection methods, but with better incremental accuracy, faster time-to-detection and less computational overhead. We evaluate its performance using incremental metrics and propose new repair processing evaluation standards.
DA  - 2014
LA  - eng
PY  - 2014
TI  - Strongly Incremental Repair Detection
UR  - https://nbn-resolving.org/urn:nbn:de:0070-pub-27004369
Y2  - 2024-11-22T00:35:18
ER  -