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Using neural networks for vector quantization in low rate speech coders

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2 Author(s)
Thyssen, J. ; Telecommun. Res. Lab., Horsholm, Denmark ; Hansen, S.D.

The problem of reducing the complexity of the codebook search in low-rate speech coders is addressed. Emphasis is placed on vector quantization of the short-term parameters (spectral parameters), where the increasing demand for higher performance necessitates codebook sizes of approximately 2/sup 20/. As full search is impractical, a novel path search algorithm is proposed. it is based on a multidimensional version of Kohonen's self-organizing feature map, using the ordering aspects of the map. A comparison with the full-search LBG algorithm shows a substantial reduction in search complexity with only a minor degradation in speech quality. Furthermore, the speech quality is better than that obtained with split-LBG.<>

Published in:

Acoustics, Speech, and Signal Processing, 1993. ICASSP-93., 1993 IEEE International Conference on  (Volume:2 )

Date of Conference:

27-30 April 1993