• DocumentCode
    3582852
  • Title

    Multipitch tracking with continuous correlation feature and hybrid DBNS/HMM model

  • Author

    Jie Lin ; Gen Zhang ; Bo Fu ; Yujie Hao

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • fYear
    2014
  • Firstpage
    218
  • Lastpage
    221
  • Abstract
    This paper proposed a new approach used for tracking multi-pith within one mixture speech signal. In this method, we employed a novel continuous correlation feature for calculating pitch model. This feature not only represents the harmonicity but also includes the information of spectral continuity, and hence improving the accuracy of the multi-pitch estimate. A DBNs and HMM hybrid model was further utilized to construct pitch models for determining pitch states and search for the best pitch state sequence. The new approach has been evaluated on mixture speech data and the results demonstrated its efficiency.
  • Keywords
    belief networks; estimation theory; hidden Markov models; speech processing; continuous correlation feature; deep belief network; hidden Markov model; hybrid DBNS-HMM model; mixture speech data; multipitch estimate; multipitch tracking; pitch state sequence; spectral continuity; speech signal; Acoustics; Correlation; Hidden Markov models; Signal processing algorithms; Speech; Speech processing; Vectors; HMM; Pitch detection; deep belief network; multi-pitch tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 2014 11th International Computer Conference on
  • Print_ISBN
    978-1-4799-7207-4
  • Type

    conf

  • DOI
    10.1109/ICCWAMTIP.2014.7073394
  • Filename
    7073394