• DocumentCode
    1835654
  • Title

    Speech synthesis using artificial neural networks

  • Author

    Raghavendra, E. Veera ; Vijayaditya, P. ; Prahallad, K.

  • Author_Institution
    Int. Inst. of Inf. Technol., Hyderabad, India
  • fYear
    2010
  • fDate
    29-31 Jan. 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Statistical parametric synthesis becoming more popular in recent years due to its adaptability and size of the synthesis. Mel cepstral coefficients, fundamental frequency (f0) and duration are the main components for synthesizing speech in statistical parametric synthesis. The current study mainly concentrates on mel cesptral coefficients. Durations and f0 are taken from the original data. In this paper, we are attempting on two fold problem. First problem is how to predict mel cepstral coefficient from text using artificial neural networks. The second problem is predicting formants from the text.
  • Keywords
    cepstral analysis; neural nets; speech synthesis; statistical analysis; Mel cepstral coefficients; artificial neural networks; fundamental frequency; speech synthesis; statistical parametric synthesis; Acoustic waves; Artificial neural networks; Bandwidth; Cepstral analysis; Hidden Markov models; Network synthesis; Predictive models; Signal synthesis; Speech synthesis; Vocoders; formants; speech synthesis; statistical parametric speech synthesis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (NCC), 2010 National Conference on
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4244-6383-1
  • Type

    conf

  • DOI
    10.1109/NCC.2010.5430190
  • Filename
    5430190