Vector quantization and perceptual criteria for low-rate coding of speech

Considerable effort has been and is currently being concentrated on improving the speech quality at low and very low bit rates. Recently new models of LPC excitation have been devised, which are able to yield good quality speech by exploiting our knowledge of the human speech production and perception processes. Unfortunately, these models generally require too much computational load to be easily implemented on currently available hardware. This paper describes an efficient speech coder, capable of providing acceptable quality speech, within the limitations of both low bit rate (approximately 2.4 kbit/s) and real-time implementation. The coder is based upon pattern classification and cluster analysis with perceptually-meaningful error minimization criteria. Our main objective is improving the excitation representation in a linear predictive coding scheme and, hence, the subjective quality of synthesized speech signals.