Abstract

In this paper, we present approaches used in text summarization, showing how they can be adapted for speech summarization and where they fall short. Informal style and apparent lack of structure in speech mean that the typical approaches used for text summarization must be extended for use with speech. We illustrate how features derived from speech can help determine summary content within two ongoing summarization projects at Columbia University.

Keywords:
Automatic summarization Computer science Natural language processing Multi-document summarization Artificial intelligence Speech recognition Style (visual arts) Information retrieval

Metrics

70
Cited By
5.50
FWCI (Field Weighted Citation Impact)
25
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Speech and dialogue systems
Physical Sciences →  Computer Science →  Artificial Intelligence

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