Government of Canada
Symbol of the Government of Canada

Common menu bar links

The NRC Publications Archive is now operational; however, not all the features of the site are available at this time.

The following features remain unavailable:

  • Viewing/Downloading of full text publications
  • Author browse feature
  • Affiliation/institute/portfolio search
  • NRC Publication Archive statistics

NRC is currently working to restore these features and we will update this notice as these features become available. Thank you for your patience.


Spotting keywords and sensing topic changes in speech

Alternate title:
Spotting keywords and censoring topic changes in speech
Information and Communication Technologies; National Research Council Canada
Conference publication
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
Pages :
NPArC #:
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.
Bookmark and Share:
HTML Link: