• DocumentCode
    2831962
  • Title

    A Speech/Music/Silence/Garbage/ Classifier for Searching and Indexing Broadcast News Material

  • Author

    Patsis, Yorgos ; Verhelst, Werner

  • Author_Institution
    Dept. ETRO, Vrije Univ. Brussel, Brussels
  • fYear
    2008
  • fDate
    1-5 Sept. 2008
  • Firstpage
    585
  • Lastpage
    589
  • Abstract
    An audio classifier that can distinguish between speech, music, silence and garbage has been developed. The classifier was trained and tested on broadcast news material provided by VRT (Flemish Radio and Television Network). Several feature sets and machine learning algorithms have been tested, providing choices of speed and performance for a target system. The audio classifier is part of a greater system that together with visual data can retrieve information from news broadcasts: speech can be converted to text and the speaker can be recognized. Music can be further used for genre classification, jingle recognition or copyright infringement detection. Silence is recognized and used to provide cues on topic changes or speaker turns. At this point everything that is not classified as speech, music or silence is labeled garbage. Garbage classes can be further used for background categorization giving information on the environment where someone speaks (an anchor in the studio or a reporter in the street).
  • Keywords
    audio signal processing; indexing; information retrieval; learning (artificial intelligence); signal classification; audio classifier; background categorization; broadcast news material; indexing; information retrieval; machine learning; searching; speech-music-silence-garbage classifier; Audio databases; Entropy; Expert systems; Frequency; Indexing; Music; Radio broadcasting; Signal detection; Speech processing; TV broadcasting; Audio Classification; Broadcast News;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Database and Expert Systems Application, 2008. DEXA '08. 19th International Workshop on
  • Conference_Location
    Turin
  • ISSN
    1529-4188
  • Print_ISBN
    978-0-7695-3299-8
  • Type

    conf

  • DOI
    10.1109/DEXA.2008.104
  • Filename
    4624780