Spoken Versus Typed Human and Computer Dialogue Tutoring
International Journal of Artificial Intelligence in Education
ITSPOKE: an intelligent tutoring spoken dialogue system
HLT-NAACL--Demonstrations '04 Demonstration Papers at HLT-NAACL 2004
A finite-state turn-taking model for spoken dialog systems
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Prosodic turn-yielding cues with and without optical feedback
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Turn-yielding cues in task-oriented dialogue
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Importance-Driven Turn-Bidding for spoken dialogue systems
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Opensmile: the munich versatile and fast open-source audio feature extractor
Proceedings of the international conference on Multimedia
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Most spoken dialogue systems are still lacking in their ability to accurately model the complex process that is human turntaking. This research analyzes a human-human tutoring corpus in order to identify prosodic turn-taking cues, with the hopes that they can be used by intelligent tutoring systems to predict student turn boundaries. Results show that while there was variation between subjects, three features were significant turn-yielding cues overall. In addition, a positive relationship between the number of cues present and the probability of a turn yield was demonstrated.