Spotting keywords and sensing topic changes in speech
Spotting keywords and censoring topic changes in speech
Information and Communication Technologies; National Research Council Canada
IEEE Symposium on Computational Intelligence for Security and Defence Applications (CISDA 2012), July 11-13, 2012, Ottawa, Ontario, Canada
CISDA 2012: Proceedings of the IEEE Symposium on Computational Intelligence for Security and Defence Applications
keyword spotting; topic segmentation; speech understanding
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.