• DocumentCode
    2910924
  • Title

    Developing Bengali Speech Corpus for Phone Recognizer Using Optimum Text Selection Technique

  • Author

    Mandal, Sandipan ; Das, Biswajit ; Mitra, Pabitra ; Basu, Anupam

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Indian Inst. of Technol., Kharagpur, India
  • fYear
    2011
  • fDate
    15-17 Nov. 2011
  • Firstpage
    268
  • Lastpage
    271
  • Abstract
    Speech corpus plays a key role in construction of automatic speech recognition (ASR), text-to-speech (TTS) synthesis and phone recognition (PR) system. PR system and ASR system are quite similar in functionality. The difference between these two is that for PR system the speech signal is converted to phonefootnote{smallest discrete segment of sound in uttered speech} text whereas for ASR system the speech signal is converted to word text. Speech corpus for PR system usually consists of a text corpus, recording data corresponding to the text corpus, phonetic representation of the text corpus and a pronunciation dictionary. Selecting optimum text from available text with balanced phone distribution is an important task for developing high quality PR system. In this paper, we describe our text selection technique and discuss the performance of phone recognition system.
  • Keywords
    speech recognition; speech synthesis; text analysis; ASR system; Bengali speech corpus; PR system; automatic speech recognition system; balanced phone distribution; phone recognition system; phone recognizer; phone-footnote text; phonetic representation; pronunciation dictionary; speech signal; text corpus; text selection technique; text-to-speech synthesis system; Accuracy; Computational modeling; Dictionaries; Hidden Markov models; Speech; Speech recognition; Text recognition; GMM; HMM; MFCC; phoneme; sphinx3; sphinxtrain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Asian Language Processing (IALP), 2011 International Conference on
  • Conference_Location
    Penang
  • Print_ISBN
    978-1-4577-1733-8
  • Type

    conf

  • DOI
    10.1109/IALP.2011.16
  • Filename
    6121518