2017
EACL
EACL 2017
Joint, Incremental Disfluency Detection and Utterance Segmentation from Speech
Abstract
AbstractWe 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.
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Interdisciplinary Bridge
— Artificial Intelligence and Computer Vision and Machine Learning and Natural Language Processing and Speech & Audio
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Keyword Pioneer
— utterance segmentation
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Artificial Intelligence > Core AI > Agent Systems
Computer Vision > Processing > Video Processing
Natural Language Processing > Applications > Text Classification
Machine Learning > Learning Types > Multi-Task Learning
Natural Language Processing > Applications > Dialogue Systems
Speech & Audio > Analysis > Speech Analysis