吉林大学学报(工学版) ›› 2012, Vol. 42 ›› Issue (01): 223-227.

• paper • Previous Articles     Next Articles

Fast and low-storage vector quantizer of line spectral frequency coefficients

LIANG Yan-xia1,2, YANG Jia-wei2, LI Ye2, NIE Min1, LIU Xin3   

  1. 1. School of Communication and Information Engineering,Xi'an Institute of Post and Telecommunication,Xi'an 710121,China;
    2. State Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710071, China;
    3. ZTE Corporation,Xi'an 710065,China
  • Received:2010-06-02 Online:2012-01-01 Published:2012-01-01

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Abstract:

A fast and low-storage vector quantizer was developed to quantize line spectral frequency (LSF) coefficients. It reduces the storage and searching complexity of codebooks by better use of the inter and intra frame correlations of LSF coefficients. After the average value was removed, LSF coefficients were predicted by a first order moving average predictor. Then the residual LSF coefficients were quantized by a three-stage vector quantizer. In the second stage, each high-dimensional LSF coefficient vector was slit into low-dimensional parts, which were quantized by different codebooks to reduce the storage and searching complexity of the codebooks. Simulation by C programming language demonstrates that the average spectral distortion is 0.91 dB, the percentage of outlier between 2 dB and 4 dB is 0.13% under the condition of low bit rate speech coding. Both storage and searching complexity of codebooks are reduced more than 31%.

Key words: information processing, speech coding, moving average predictor, vector quantization, spectral distortion

CLC Number: 

  • TN912.3


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