ACL Anthology

Automatic Segmentation of Multiparty Dialogue

12 years 5 months ago
Automatic Segmentation of Multiparty Dialogue
In this paper, we investigate the problem of automatically predicting segment boundaries in spoken multiparty dialogue. We extend prior work in two ways. We first apply approaches that have been proposed for predicting top-level topic shifts to the problem of identifying subtopic boundaries. We then explore the impact on performance of using ASR output as opposed to human transcription. Examination of the effect of features shows that predicting top-level and predicting subtopic boundaries are two distinct tasks: (1) for predicting subtopic boundaries, the lexical cohesion-based approach alone can achieve competitive results, (2) for predicting top-level boundaries, the machine learning approach that combines lexical-cohesion and conversational features performs best, and (3) conversational cues, such as cue phrases and overlapping speech, are better indicators for the toplevel prediction task. We also find that the transcription errors inevitable in ASR output have a negative impact ...
Pei-yun Hsueh, Johanna D. Moore, Steve Renals
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where EACL
Authors Pei-yun Hsueh, Johanna D. Moore, Steve Renals
Comments (0)