The additive effect of turn-taking cues in human and synthetic voice
Speech Communication
Turn-taking cues in task-oriented dialogue
Computer Speech and Language
Overlap in meetings: ASR effects and analysis by dialog factors, speakers, and collection site
MLMI'06 Proceedings of the Third international conference on Machine Learning for Multimodal Interaction
Transcribing Meetings With the AMIDA Systems
IEEE Transactions on Audio, Speech, and Language Processing
Proceedings of the 15th ACM on International conference on multimodal interaction
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Overlapping talk occurs frequently in multi-party conversations, and is a domain in which speakers may pursue various communicative goals. The current study focuses on turn competition. Specifically, we seek to identify the phonetic differences that discriminate turn-competitive from non-competitive overlaps. Conversation analysis techniques were used to identify competitive and non-competitive overlaps in a corpus of multi-party recordings. We then generated a set of potentially predictive features relating to prosody (F0, intensity, speech rate, pausing) and overlap placement (overlap duration, point of overlap onset, recycling etc.). Decision tree classifiers were trained on the features and tested on a classification task, in order to determine which features and feature combinations best differentiate competitive overlaps from non-competitive overlaps. It was found that overlap placement features played a greater role than prosodic features in indicating turn competition. Among the prosodic features tested, F0 and intensity were the most effective predictors of turn competition. Also, our decision tree models suggest that turn competitive and non-competitive overlaps can be initiated by a new speaker at many different points in the current speaker's turn. These findings have implications for the design of dialogue systems, and suggest novel hypotheses about how speakers deploy phonetic resources in everyday talk.