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.
CITATION STYLE
Hough, J., & Schlangen, D. (2017). Joint, incremental disfluency detection & utterance segmentation from speech. In 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference (Vol. 1, pp. 326–336). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/e17-1031
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