8th Annual Conference of the International Speech Communication Association

Antwerp, Belgium
August 27-31, 2007

Speaker Adaptation of Language Models for Automatic Dialog Act Segmentation of Meetings

Jáchym Kolář (1), Yang Liu (2), Elizabeth Shriberg (3)

(1) University of West Bohemia, Czech Republic
(2) University of Texas at Dallas, USA
(3) SRI International, USA

Dialog act (DA) segmentation in meeting speech is important for meeting understanding. In this paper, we explore speaker adaptation of hidden event language models (LMs) for DA segmentation using the ICSI Meeting Corpus. Speaker adaptation is performed using a linear combination of the generic speaker-independent LM and an LM trained on only the data from individual speakers. We test the method on 20 frequent speakers, on both reference word transcripts and the output of automatic speech recognition. Results indicate improvements for 17 speakers on reference transcripts, and for 15 speakers on automatic transcripts. Overall, the speaker-adapted LM yields statistically significant improvement over the baseline LM for both test conditions.

Full Paper

Bibliographic reference.  Kolář, Jáchym / Liu, Yang / Shriberg, Elizabeth (2007): "Speaker adaptation of language models for automatic dialog act segmentation of meetings", In INTERSPEECH-2007, 1621-1624.