Spotting keywords and sensing topic changes in speech

Alternative titleSpotting keywords and censoring topic changes in speech
Download
  1. (PDF, 264 KB)
DOIResolve DOI: http://doi.org/10.1109/CISDA.2012.6291537
AuthorSearch for:
TypeArticle
Proceedings titleCISDA 2012: Proceedings of the IEEE Symposium on Computational Intelligence for Security and Defence Applications
ConferenceIEEE Symposium on Computational Intelligence for Security and Defence Applications (CISDA 2012), July 11-13, 2012, Ottawa, Ontario, Canada
ISBN978-1-4673-1416-9
Pages17; # of pages: 7
Subjectkeyword spotting; topic segmentation; speech understanding
AbstractSecurity 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.
Publication date
PublisherIEEE
LanguageEnglish
AffiliationInformation and Communication Technologies; National Research Council Canada
Peer reviewedYes
NPARC number20794317
Export citationExport as RIS
Report a correctionReport a correction
Record identifier0c7d411a-efcb-4e7c-9674-02a22949eacb
Record created2012-10-12
Record modified2016-05-09
Bookmark and share
  • Share this page with Facebook (Opens in a new window)
  • Share this page with Twitter (Opens in a new window)
  • Share this page with Google+ (Opens in a new window)
  • Share this page with Delicious (Opens in a new window)