Abstract
This paper presents an analysis of named entity recognition and classification in spontaneous speech transcripts. We annotated a significant fraction of the Switchboard corpus with six named entity classes and investigated a battery of machine learning models that include lexical, syntactic, and semantic attributes. The best recognition and classification model obtains promising results, approaching within 5% a system evaluated on clean textual data.
Original language | English (US) |
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Pages | 3433-3436 |
Number of pages | 4 |
State | Published - Dec 1 2005 |
Externally published | Yes |
Event | 9th European Conference on Speech Communication and Technology - Lisbon, Portugal Duration: Sep 4 2005 → Sep 8 2005 |
Other
Other | 9th European Conference on Speech Communication and Technology |
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Country | Portugal |
City | Lisbon |
Period | 9/4/05 → 9/8/05 |
ASJC Scopus subject areas
- Engineering(all)