Abstract
This paper is about a system that extracts principal content words from speech-recognized transcripts of voicemail messages and classifies them into proper names, telephone numbers, dates/times and `other'. 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 being identified by a vector of lexical and prosodic features. The features are selected using Parcel, an ROC-based algorithm. We visually compare the role of a large number of individual features and discuss effective ways to combine them. We finally evaluate their performance on manual and automatic transcriptions derived from two different speech recognition systems.
| Original language | English |
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| Title of host publication | Proceedings of the 8th European Conference on Speech Communication and Technology |
| Subtitle of host publication | Eurospeech 2003 - Interspeech 2003 |
| Publisher | ISCA |
| Pages | 2785-2788 |
| Number of pages | 4 |
| Publication status | Published - 2003 |
| Event | 8th European Conference on Speech Communication and Technology (Eurospeech 2003) - Geneva, Switzerland Duration: 1 Sept 2003 → 4 Sept 2003 |
Conference
| Conference | 8th European Conference on Speech Communication and Technology (Eurospeech 2003) |
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| Country/Territory | Switzerland |
| City | Geneva |
| Period | 1/09/03 → 4/09/03 |