• DocumentCode
    2660390
  • Title

    A similar content retrieval method for podcast episodes

  • Author

    Mizuno, Junta ; Ogata, Jun ; Goto, Masataka

  • Author_Institution
    Nara Inst. of Sci. & Technol., Ikoma
  • fYear
    2008
  • fDate
    15-19 Dec. 2008
  • Firstpage
    297
  • Lastpage
    300
  • Abstract
    Given podcasts (audio blogs) that are sets of speech files called episodes, this paper describes a method for retrieving episodes that have similar content. Although most previous retrieval methods were based on bibliographic information, tags, or users´ playback behaviors without considering spoken content, our method can compute content-based similarity based on speech recognition results of podcast episodes even if the recognition results include some errors. To overcome those errors, it converts intermediate speech-recognition results to a confusion network containing competitive candidates, and then computes the similarity by using keywords extracted from the network. Experimental results with episodes that have different word accuracy and content showed that keywords obtained from competitive candidates were useful in retrieving similar episodes. To show relevant episodes, our method will be incorporated into PodCastle, a public web service that provides full-text searching of podcasts on the basis of speech recognition.
  • Keywords
    content-based retrieval; information retrieval; speech recognition; audio blogs; bibliographic information; confusion network; content-based similarity; keywords extraction; podcast episodes; retrieval methods; similar content retrieval; speech files; speech recognition; Blogs; Computer networks; Content based retrieval; Digital audio broadcasting; Digital audio players; Feeds; Information retrieval; Speech recognition; Uniform resource locators; Web services; Confusion network; Content-based similarity; Podcast; Speech recognition; Spoken document retrieval;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Spoken Language Technology Workshop, 2008. SLT 2008. IEEE
  • Conference_Location
    Goa
  • Print_ISBN
    978-1-4244-3471-8
  • Electronic_ISBN
    978-1-4244-3472-5
  • Type

    conf

  • DOI
    10.1109/SLT.2008.4777899
  • Filename
    4777899