Title :
Fast and low-complexity LSF quantization using algebraic vector quantizer
Author :
Xie, Minjie ; Adoul, Jean-Pierre
Author_Institution :
Dept. of Electr. & Comput. Eng., Sherbrooke Univ., Que., Canada
Abstract :
This paper presents an algebraic vector-quantization scheme for encoding the LSF parameters used in describing the time-varying short-term spectrum of speech in many modern vocoders. The quantizer achieves an average spectral distortion of 1 dB at 28 bits/frame for the telephone bandwidth. The scheme is based on low-dimensionality regular-point lattices. The properties of lattices are taken advantage of in both the design and the search of the quantizer codebook. Namely, this algebraic codebook need not be stored in memory and the optimum vector is found through simple rounding of the input variables instead of the usual exhaustive search. Thus, the scheme results in significant savings of memory and reduced computational complexity when compared to traditional vector-quantizer solutions
Keywords :
algebraic codes; computational complexity; linear predictive coding; spectral analysis; speech coding; speech processing; vector quantisation; vocoders; LPC; LSF parameters encoding; algebraic codebook; algebraic vector quantizer; algebraic vector-quantization; average spectral distortion; computational complexity reduction; fast LSF quantization; input variables rounding; low-complexity LSF quantization; low-dimensionality regular-point lattices; memory reduction; quantizer codebook; speech spectrum; telephone bandwidth; time-varying short-term spectrum; vocoders; Algorithm design and analysis; Encoding; Filters; Frequency; Lattices; Linear predictive coding; Polynomials; Speech analysis; Speech coding; Vector quantization;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.479794