The importance of integrating voice and data over digital networks has increased during the last few years primarily because of the growing popularity of such networks. Of particular interest are efficient voice digitizing terminals, capable of operating at various data rates in both circuit-switched and packet-switched data networks. Several such terminals, including two or more speech compression algorithms, have been proposed and implemented. Typically the terminal switches between a low-rate (500 - 4000 bits/s) vocoding scheme and a medium-rate (7000 - 16000 bits/s) waveform coding algorithm, depending on, among other things, the network congestion and on the desired voice quality and robustness. We here describe the design and simulation of a multirate voice digitizer (MRVD) that switches between two speech compression systems, each based on a recently developed vector quantization (VQ) coding technique. This technique consists of the off-line interactive design of a codebook minimizing an average distortion measure, followed by the use of the codebook in an on-line nearest neighbor encoding scheme. One of the two systems is a rate-distortion speech coder that resembles a linear predictive coding (LPC) speech compression system but has a much lower rate (800 bits/s and below). We call this the LPC-VQ system, and it is similar to other previously reported systems [15],[19],[21]. The only difference is that the LPC parameters are extracted using the Burg method instead of the autocorrelation method. We here show that this provides both qualitative and quantitative improvements. The other system of our MRVD is a residual-excited linear predictive (RELP) speech compression system using VQ in both model selection and residual digitization. The residual waveform is digitized at 1 or 2 bits/sample, resulting in rates of 7300 and 13800 bits/s, respectively. We call this the RELP-VQ system. When compared to other RELP systems [6]-[8], it is shown to have a simpler architecture and to provide comparable speech quality. In a direct comparison with an APC scheme, our RELP-VQ system was determined to provide a more natural speech sound. Another interesting result presented is the quantitative comparison of the application of the VQ algorithm to the original speech waveform and its residuals.

An algorithm for the design of locally optimum vector quantizers relative to a distortion measure is used to design and simulate vector quantizers for both real sampled speech and for speech-like waveforms produced by a tenth order autoregressive random process with matching autocorrelation. Both squared-error and a weighted squared error were considered. The experimental results were compared with performance bounds from rate distortion theory based on the autoregressive model.

An information theory approach to the theory and practice of linear predictive coded (LPC) speech compression systems is developed. It is shown that a traditional LPC system can be viewed as a minimum distortion or nearest-neighbor system where the distortion measure is a minimum discrimination information between a speech process model and an observed frame of actual speech. This distortion measure is used in an algorithm for computer-aided design of block source codes subject to a fidelity criterion to obtain a 750-bits/s speech compression system that resembles an LPC system but has a much lower rate, a larger memory requirement, and requires no on-line LPC analysis. Quantitative and informal subjective comparisons are made among our system and LPC systems.