• DocumentCode
    624680
  • Title

    Pitch detection using EMD-based AMDF

  • Author

    Yuan Zong ; Yumin Zeng ; Mengchao Li ; Rui Zheng

  • Author_Institution
    Sch. of Phys. & Technol., Nanjing Normal Univ., Nanjing, China
  • fYear
    2013
  • fDate
    9-11 June 2013
  • Firstpage
    594
  • Lastpage
    597
  • Abstract
    This paper presents a new modified average magnitude difference function (AMDF) based on empirical mode decomposition (EMD) for pitch detection. We call it EMD-based AMDF (EMDAMDF). EMDAMDF inherits lots of advantages successfully from the conventional AMDF and eliminates the falling trend of the AMDF adaptively by means of EMD. Based on EMDAMDF, an effective pitch detection algorithm is proposed. The simulated results on Keele pitch reference database shows that the performance of the proposed EMDAMDF based pitch detection algorithm is obviously better than the original AMDF and its improvements (such as CAMDF and EAMDF) based algorithms.
  • Keywords
    audio databases; spectral analysis; speech processing; CAMDF based algorithm; EAMDF based algorithm; EMD-Based AMDF; EMDAMDF based pitch detection algorithm; Keele pitch reference database; empirical mode decomposition; modified average magnitude difference function; Accuracy; Databases; Detection algorithms; Empirical mode decomposition; Market research; Signal to noise ratio; Speech; AMDF; EMD; EMDAMDF; pitch detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Information Processing (ICICIP), 2013 Fourth International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-6248-1
  • Type

    conf

  • DOI
    10.1109/ICICIP.2013.6568144
  • Filename
    6568144