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Spotting keywords and sensing topic changes in speech

 
 
Alternate title:
Spotting keywords and censoring topic changes in speech
Affiliation:
Information and Communication Technologies; National Research Council Canada
Language:
English
Type:
Conference publication
Conference:
IEEE Symposium on Computational Intelligence for Security and Defence Applications (CISDA 2012), July 11-13, 2012, Ottawa, Ontario, Canada
Proceedings
Title:
CISDA 2012: Proceedings of the IEEE Symposium on Computational Intelligence for Security and Defence Applications
Date:
2012
Pages :
1-7
NPArC #:
20794317
Keywords:
keyword spotting; topic segmentation; speech understanding
Abstract:
Security concerns involved in dealing with sensitive information conveyed in human languages must be able to handle speech, which is the most basic, natural form of human communication and a huge amount of data are being generated daily. Dealing with such data is naturally associated with typical big-data problems in terms of both computational complexity and storage space. Unfortunately, compared with written texts, speech is inherently more difficult to browse, if no technical support is provided. In this paper we are interested in spotting keywords, which could reflect a security agent's information needs, and study its usefulness in helping automatically disclose topic changes (boundaries) in speech data under concern. Our results show that keyword spotting can help identify topics with a competitive performance.
 
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