Joint, Incremental Disfluency Detection and Utterance Segmentation from Speech

Julian Hough, David Schlangen


Abstract
We present the joint task of incremental disfluency detection and utterance segmentation and a simple deep learning system which performs it on transcripts and ASR results. We show how the constraints of the two tasks interact. Our joint-task system outperforms the equivalent individual task systems, provides competitive results and is suitable for future use in conversation agents in the psychiatric domain.
Anthology ID:
E17-1031
Volume:
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
Month:
April
Year:
2017
Address:
Valencia, Spain
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
326–336
Language:
URL:
https://www.aclweb.org/anthology/E17-1031
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/E17-1031.pdf