On the use of hierarchical spectral dynamics in speech recognition

A vector quantization (VQ)-based recognition method which uses feature vector codebooks containing hierarchical spectral dynamics is proposed. This method is highly effective for reducing the number of candidates in word recognition and achieving a high recognition accuracy in /b/,/d/ and /g/ recognition. Since this method does not need time alignment, it has the advantage of a small amount of computation and ease of parallel processing. Experimental results comparing the performances of the multiple-codebook and single-codebook methods indicate that, when the codebook size is small, the multiple-codebook method is better than the single-codebook method. However, if the codebook size is reasonably large, the single-codebook method displays better performance than the multiple-codebook method