• DocumentCode
    1099728
  • Title

    A temporal-analysis-based pitch estimation system for noisy speech with a comparative study of performance of recent systems

  • Author

    Khurshid, Azar ; Denham, Susan L.

  • Author_Institution
    Plymouth Inst. of Neurosci., UK
  • Volume
    15
  • Issue
    5
  • fYear
    2004
  • Firstpage
    1112
  • Lastpage
    1124
  • Abstract
    In this paper, a new system of pitch estimation is presented. The system is designed to be robust to challenging noise conditions. This robustness to the presence of noise in the signal is achieved by developing a new representation of the speech signal, based on the operation of damped harmonic oscillators (DHOs), and temporal mode analysis of their output. The resulting representation is shown to possess qualities that are only gradually degraded in the presence of noise. A harmonic grouping based system is used to estimate the pitch frequency. This method is easily extended to simultaneously track the pitch of more than one speaker. In a series of experiments the accuracy and noise robustness of the proposed system was compared with that of a number of prominent pitch estimation and tracking systems. The results show that the proposed system´s overall performance is much better than any of the other systems tested, especially in the presence of very large amounts of noise. Furthermore, the proposed system is comparatively inexpensive in terms of processing and memory requirements.
  • Keywords
    correlation theory; frequency estimation; harmonic oscillators; noise; speech processing; damped harmonic oscillators; harmonic grouping based system; noise robustness; noisy speech; pitch frequency estimation; pitch tracking systems; signal noise; speech signal; temporal mode analysis; temporal-analysis-based pitch estimation system; Acoustic noise; Autocorrelation; Delay; Frequency estimation; Harmonic analysis; Noise robustness; Oscillators; Speech analysis; Speech enhancement; Speech recognition; Pitch estimation; speech processing; temporal coding;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/TNN.2004.832818
  • Filename
    1333076