Vector quantization and Markov source models applied to speech recognition

An isolated word recognizer based on vector quantization at the acoustic level and on stochastic modeling at the phonetic level is described. The power of this approach lies in its best utilization of the training data. The first experimental results obtained are encouraging and suggest that further optimization is possible.