• DocumentCode
    515396
  • Title

    Speaker Independent Urdu speech recognition using HMM

  • Author

    Ashraf, Javed ; Iqbal, Naveed ; Khattak, Naveed Sarfraz ; Zaidi, Ather Mohsin

  • Author_Institution
    Coll. of Signals, Nat. Univ. of Sci. & Technol. (NUST), Rawalpindi, Pakistan
  • fYear
    2010
  • fDate
    28-30 March 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Automatic Speech Recognition (ASR) is one of the advanced fields of Natural Language Processing (NLP). Recent past has witnessed valuable research activities in ASR in English, European and East Asian languages. But unfortunately South Asian Languages in general and ¿Urdu¿ in particular have received very less attention. In this paper we present an approach to develop an ASR system for Urdu language. The proposed system is based on an open source speech recognition framework called Sphinx4 which uses statistical based approach (Hidden Markov Model) for developing ASR system. We present a Speaker Independent ASR system for small sized vocabulary, i.e. fifty two isolated most spoken Urdu words and suggest that this research work will form the basis to develop medium and large size vocabulary Urdu speech recognition system.
  • Keywords
    hidden Markov models; natural language processing; speech recognition; ASR system; East Asian languages; English languages; European languages; HMM; South Asian Languages; Sphinx4; automatic speech recognition; hidden Markov model; natural language processing; speaker independent Urdu speech recognition; statistical based approach; Automatic speech recognition; Educational institutions; Hidden Markov models; Mathematical model; Natural language processing; Natural languages; Signal processing; Speech recognition; Strontium; Vocabulary; CMU Sphinx4; Hidden Markov Model; Speech Recognition; Urdu language;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Informatics and Systems (INFOS), 2010 The 7th International Conference on
  • Conference_Location
    Cairo
  • Print_ISBN
    978-1-4244-5828-8
  • Type

    conf

  • Filename
    5461790