Sumit Basu, Surabhi Gupta, Milind Mahajan, Patrick Nguyen, and John C. Platt
In this work, we present a novel means of browsing recorded audio conversations. The method we develop produces scalable summaries of the recognized speech, in which we can increase the amount of text continuously with the desired level of detail to best fill the available space. We present an interface in which a user can view an entire conversation in one screen, but can also quickly zoom in to see the full transcript; the corresponding audio can be easily played as well. The scaling is achieved via a combination of topic segmentation and informative phrase selection, where the threshold for informativeness decreases with increasing level of detail. Finally, we evaluate our method and interface against a baseline interface with a user study.
In IUI '08: Proceedings of the 13th international conference on Intelligent user interfaces
Publisher Association for Computing Machinery, Inc.
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