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Automatic summarization of voicemail messages using lexical and prosodic features

Automatic summarization of voicemail messages using lexical and prosodic features This aticle presents trainable methods for extracting principal content words from voicemail messages. The short text summaries generated are suitable for mobile messaging applications. The system uses a set of classifiers to identify the summary words with each word described by a vector of lexical and prosodic features. We use an ROC-based algorithm, Parcel, to select input features (and classifiers). We have performed a series of objective and subjective evaluations using unseen data from two different speech recognition systems as well as human transcriptions of voicemail speech. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Speech and Language Processing (TSLP) Association for Computing Machinery

Automatic summarization of voicemail messages using lexical and prosodic features

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References (53)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2005 by ACM Inc.
ISSN
1550-4875
DOI
10.1145/1075389.1075390
Publisher site
See Article on Publisher Site

Abstract

This aticle presents trainable methods for extracting principal content words from voicemail messages. The short text summaries generated are suitable for mobile messaging applications. The system uses a set of classifiers to identify the summary words with each word described by a vector of lexical and prosodic features. We use an ROC-based algorithm, Parcel, to select input features (and classifiers). We have performed a series of objective and subjective evaluations using unseen data from two different speech recognition systems as well as human transcriptions of voicemail speech.

Journal

ACM Transactions on Speech and Language Processing (TSLP)Association for Computing Machinery

Published: Feb 1, 2005

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