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Extractive Summarization of Voicemail using Lexical and Prosodic Feature Subset Selection

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eurospeech01.pdf (60.95Kb)
Date
2001
Author
Koumpis, Konstantinos
Renals, Steve
Niranjan, Mahesan
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Abstract
This paper presents a novel data-driven approach to summarizing spoken audio transcripts utilizing lexical and prosodic features. The former are obtained from a speech recognizer and the latter are extracted automatically from speech waveforms. We employ a feature subset selection algorithm, based on ROC curves, which examines different combinations of features at different target operating conditions. The approach is evaluated on the IBM Voicemail corpus, demonstrating that it is possible and desirable to avoid complete commitment to a single best classifier or feature set.
URI
http://www.isca-speech.org/archive/eurospeech_2001/index.html

http://hdl.handle.net/1842/1145
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