On Speaker-Specific Prosodic Models for Automatic Dialog Act Segmentation of Multi-Party Meetings

TitleOn Speaker-Specific Prosodic Models for Automatic Dialog Act Segmentation of Multi-Party Meetings
Publication TypeConference Paper
Year of Publication2006
AuthorsKolar, J., Shriberg E., & Liu Y.
Published inProceedings of the 9th International Conference on Spoken Language Processing (ICSLP-Interspeech 2006)
Page(s)2014-2017
Other Numbers2055
Abstract

We explore speaker-specific prosodic modeling for dialog act segmentation of speech from the ICSI Meeting Corpus. We ask whether features beyond pauses help individual speakers, and whether some speakers benefit from prosody models trained on only their speech. We find positive results for both questions, although the second is more complex. Feature analysis reveals that duration is the most used feature type, followed by pause and pitch features. Results also suggest a difference between native and nonnative speakers in feature usage patterns. We conclude that features beyond pauses are useful for dialog act segmentation in natural conversation, and that for some speakers, speaker-specific training yields further gains.

URLhttp://www.icsi.berkeley.edu/pubs/speech/kolar06icslp.pdf
Bibliographic Notes

Proceedings of the 9th International Conference on Spoken Language Processing (ICSLP-Interspeech 2006), Pittsburgh, Pennsylvania, pp. 2014-2017

Abbreviated Authors

J. Kolar, E. Shriberg, and Y. Liu

ICSI Research Group

Speech

ICSI Publication Type

Article in conference proceedings