• DocumentCode
    1351925
  • Title

    Joint quantisation strategies for low bit-rate sinusoidal coding

  • Author

    Unver, E. ; Villette, S. ; Kondoz, Ahme

  • Author_Institution
    Centre of Commun. Syst. Res., Univ. of Surrey, Guildford, UK
  • Volume
    4
  • Issue
    5
  • fYear
    2010
  • Firstpage
    548
  • Lastpage
    559
  • Abstract
    Although there are speech coding standards producing high-quality speech above 4 kbps, below that transparent quality has not been achieved yet. There is still room for improvement at lower bit rates, especially at 2.4 kbps and below, which is an area of interest for military and security applications. Strategies for achieving high-quality speech using sinusoidal coding at very low bit rates are discussed. Previous work in the literature on combining several frames in a metaframe and performing variable bit allocation within the metaframe is extended. Experiments have been carried out to find an optimum metaframe size compromise between delay and quantisation gains. Metaframe classification and quantisation according to the metaframe class are used for better efficiency. A method for voicing determination from the linear prediction coefficient (LPC) shape is also presented. The proposed techniques have been applied to the SB-LPC vocoder to produce speech at 1.2 and 0.8 kbps, and compared to the original SB-LPC vocoder at 2.4/1.2 kbps as well as an established standard (Mixed Excitation Linear Predictive - MELP - vocoder) at 2.4/1.2/0.6 kbps in a listening test. It has been found that the proposed techniques have been effective in reducing the bit rate while not compromising the speech quality.
  • Keywords
    linear predictive coding; speech coding; vocoders; SB-LPC vocoder; linear prediction coefficient; low bit-rate sinusoidal coding; metaframe classification; metaframe quantisation strategies; mixed excitation linear predictive vocoder; speech coding; speech quality;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IET
  • Publisher
    iet
  • ISSN
    1751-9675
  • Type

    jour

  • DOI
    10.1049/iet-spr.2009.0077
  • Filename
    5602923