• DocumentCode
    2973175
  • Title

    Comparing automatic rich transcription for Portuguese, Spanish and English Broadcast News

  • Author

    Batista, Fernando ; Trancoso, Isabel ; Mamede, Nuno J.

  • Author_Institution
    Spoken Language Syst. Lab., INESC ID Lisboa, Lisbon, Portugal
  • fYear
    2009
  • fDate
    Nov. 13 2009-Dec. 17 2009
  • Firstpage
    540
  • Lastpage
    545
  • Abstract
    This paper describes and evaluates a language independent approach for automatically enriching the speech recognition output with punctuation marks and capitalization information. The two tasks are treated as two classification problems, using a maximum entropy modeling approach, which achieves results within state-of-the-art. The language independence of the approach is attested with experiments conducted on Portuguese, Spanish and English broadcast news corpora. This paper provides the first comparative study between the three languages, concerning these tasks.
  • Keywords
    broadcasting; linguistics; maximum entropy methods; natural language processing; speech recognition; English broadcast news; English language; Portuguese broadcast news; Portuguese language; Spanish broadcast news; Spanish language; automatic rich transcription; capitalization information; language independence; maximum entropy modeling; punctuation mark; speech recognition; Automatic speech recognition; Broadcasting; Ear; Entropy; Hidden Markov models; Model driven engineering; NIST; Natural languages; Speech analysis; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automatic Speech Recognition & Understanding, 2009. ASRU 2009. IEEE Workshop on
  • Conference_Location
    Merano
  • Print_ISBN
    978-1-4244-5478-5
  • Electronic_ISBN
    978-1-4244-5479-2
  • Type

    conf

  • DOI
    10.1109/ASRU.2009.5373371
  • Filename
    5373371