Paper: Intra-Speaker Topic Modeling for Improved Multi-Party Meeting Summarization with Integrated Random Walk

ACL ID N12-1041
Title Intra-Speaker Topic Modeling for Improved Multi-Party Meeting Summarization with Integrated Random Walk
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2012
Authors

This paper proposes an improved approach to extrac- tive summarization of spoken multi-party interac- tion, in which integrated random walk is performed on a graph constructed on topical/ lexical relations. Each utterance is represented as a node of the graph, and the edges? weights are computed from the topi- cal similarity between the utterances, evaluated us- ing probabilistic latent semantic analysis (PLSA), and from word overlap. We model intra-speaker topics by partially sharing the topics from the same speaker in the graph. In this paper, we perform ex- periments on automatically and manually generated transcripts. For automatic transcripts, our results show that intra-speaker topic sharing and integrating topical/ lexical relations can help include the impor- tant utterances.