Real-time speech compression with a VLSI vector quantization processor

Vector Quantization is an attractive block coding scheme which allows more efficient use of a given channel capacity. The computational complexity of the codebook search, however, limits the practical applications of Vector Quantization -- especially in real-time situations. This paper presents a special purpose processing architecture which supports real-time search of large codebooks. The core of the computation required for a squared-error distortion measure is accomplished using a VLSI pattern matching chip. We describe a pipeline architecture which reduces the effective computation time for a single vector component to one period. The chip supports a selectable vector dimension of 2, 4, 8, or 8 and can be used with any codebook size consistent with the input vector rate and the chip´s throughput. We have built and tested a 4-micron NMOS chip which supports up to four million squared-error distance calculations per second. We outline three approaches to real-time Vector quantization which use this chip to do the pattern matching: two waveform coding processors using Vector Pulse Code Modulation and Adaptive Vector Predictive Coding, and a novel approach to rapid codebook design.