2016
INTERSPEECH
INTERSPEECH 2016
Respiratory Turn-Taking Cues
Abstract
This paper investigates to what extent breathing can be used as a cue to turn-taking behaviour. The paper improves on existing accounts by considering all possible transitions between speaker states (silent, speaking, backchanneling) and by not relying on global speaker models. Instead, all features (including breathing range and resting expiratory level) are estimated in an incremental fashion using the left-hand context. We identify several inhalatory features relevant to turn-management, and assess the fit of models with these features as predictors of turn-taking behaviour.
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Conference Pioneer
— INTERSPEECH 2016
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Keyword Pioneer
— incremental processing
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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, Speech & Audio
Authors
Keywords
speech analysis
predictive modeling
incremental processing
speaker state
speech production
speech feature
breathing pattern
respiratory analysis
incremental estimation
incremental modeling
incremental feature
respiratory feature
speaking state
respiratory pattern
incremental feature estimation
speaker state prediction
conversational turn-taking
respiratory behavior
speaker state analysis
speaker state transition
incremental analysis
inhalatory feature