Spotting keywords and sensing topic changes in speech

Xiaodan Zhu
2012 2012 IEEE Symposium on Computational Intelligence for Security and Defence Applications  
Vous avez des questions? Nous pouvons vous aider. Pour communiquer directement avec un auteur, consultez la première page de la revue dans laquelle son article a été publié afin de trouver ses coordonnées. Si vous n'arrivez pas à les repérer, communiquez avec nous à PublicationsArchive-ArchivesPublications@nrc-cnrc.gc.ca. Abstract Security concerns involved in dealing with sensitive information conveyed in human languages cannot circumvent speech, which is the most basic, natural form of human
more » ... ural form of human communication and a huge amount of data are 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.
doi:10.1109/cisda.2012.6291537 dblp:conf/cisda/Zhu12 fatcat:n27xc54osrdaxdwmsatkou3v6e