Vector quantization for a speech transform coder

摘要

A vector quantizing apparatus, a decoding apparatus, a vector quantization method, and a decoding method are provided. Upon encoding of a speech signal by the vector quantization apparatus and method, the advantages of vector quantization are maximized by quantizing the speech signal using KLT-based classified codebooks and the eigenvalues and eigenvectors of the speech signal. The vector quantization apparatus includes a codebook group, a Karhunen-Loève Transform (KLT) unit, first and second selection units and a transmission unit. The codebook group has a plurality of codebooks that store the code vectors for a speech signal, and the codebooks are classified using KLT domain statistics for the speech signal. The KLT unit transforms an input speech signal to a KLT domain. The first selection unit selects an optimal codebook from the codebooks in the codebook group on the basis of the eigenvalue set of the covariance matrix of the input speech signal obtained by KLT. The second selection unit determined the distortion between each of the code vectors in the selected codebook and the speech signal transformed to a KLT domain by the KLT unit and selects an optimal code vector on the basis of the determined distortion. The transmission unit transmits the optimal code vector so that the index of the optimal code vector is used as to reconstruct the KL-transformed input speech signal. The decoding apparatus includes a data detection unit, a codebook group, and an inverse KLT unit, and restores the original speech signal from the vector-quantized speech signal. IMAGE