We have explored the usefulness of incorporating speech and discourse features in an automatic speech summarization system applied to meeting recordings from the ICSI Meetings corpus. By analyzing speaker activity, turn-taking and discourse cues, we hypothesize that such a system can outperform solely text-based methods inherited from the field of text summarization. The summarization methods are described, two evaluation methods are applied and compared, and the results clearly show that utilizing such features is advantageous and efficient. Even simple methods relying on discourse cues and speaker activity can outperform text summarization approaches.
|Title of host publication||Proceedings of the Human Language Technology Conference of the NAACL, Main Conference|
|Place of Publication||New York City, USA|
|Publisher||Association for Computational Linguistics|
|Number of pages||8|
|Publication status||Published - 1 Jun 2006|