Automatic Summarization of Voicemail Messages Using Lexical and Prosodic Features

Konstantinos Koumpis, Steve Renals

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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.
Original languageEnglish
Article number1
Number of pages21
JournalACM Transactions on Speech and Language Processing
Issue number1
Publication statusPublished - 1 Feb 2005

Keywords / Materials (for Non-textual outputs)

  • Voicemail
  • automatic summarization
  • feature subset selection
  • prosody
  • receiver operating characteristic
  • short message service


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