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Automatic summarization of voicemail messages using lexical and prosodic features (2005)
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| Venue: | ACM Transactions on Speech and Language Processing |
| Citations: | 22 - 3 self |
BibTeX
@ARTICLE{Koumpis05automaticsummarization,
author = {Konstantinos Koumpis and Steve Renals},
title = {Automatic summarization of voicemail messages using lexical and prosodic features},
journal = {ACM Transactions on Speech and Language Processing},
year = {2005},
pages = {1--24}
}
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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.
Keyphrases
prosodic feature voicemail message automatic summarization roc-based algorithm unseen data summary word trainable method different speech recognition system voicemail speech principal content word subjective evaluation short text summary input feature human transcription mobile messaging application
