Quantization, the process of approximating continuous-amplitude signals by digital (discrete-amplitude) signals, is an important aspect of data compression or coding, the field concerned with the reduction of the number of bits necessary to transmit or store analog data, subject to a distortion or fidelity criterion. The independent quantization of each signal value or parameter is termed scalar quantization, while the joint quantization of a block of parameters is termed block or vector quantization. This tutorial review presents the basic concepts employed in vector quantization and gives a realistic assessment of its benefits and costs when compared to scalar quantization. Vector quantization is presented as a process of redundancy removal that makes effective use of four interrelated properties of vector parameters: linear dependency (correlation), nonlinear dependency, shape of the probability density function (pdf), and vector dimensionality itself. In contrast, scalar quantization can utilize effectively only linear dependency and pdf shape. The basic concepts are illustrated by means of simple examples and the theoretical limits of vector quantizer performance are reviewed, based on results from rate-distortion theory. Practical issues relating to quantizer design, implementation, and performance in actual applications are explored. While many of the methods presented are quite general and can be used for the coding of arbitrary signals, this paper focuses primarily on the coding of speech signals and parameters.

Vector quantization in speech coding

The notion of perceptual coding, which is based on the concept of distortion masking by the signal being compressed, is developed. Progress in this field as a result of advances in classical coding theory, modeling of human perception, and digital signal processing, is described. It is proposed that fundamental limits in the science can be expressed by the semiquantitative concepts of perceptual entropy and the perceptual distortion-rate function, and current compression technology is examined in that framework. Problems and future research directions are summarized. >

Signal compression based on models of human perception

The past decade has witnessed substantial progress towards the application of low-rate speech coders to civilian and military communications as well as computer-related voice applications. Central to this progress has been the development of new speech coders capable of producing high-quality speech at low data rates. Most of these coders incorporate mechanisms to: represent the spectral properties of speech, provide for speech waveform matching, and "optimize" the coder's performance for the human ear. A number of these coders have already been adopted in national and international cellular telephony standards. The objective of this paper is to provide a tutorial overview of speech coding methodologies with emphasis on those algorithms that are part of the recent low-rate standards for cellular communications. Although the emphasis is on the new low-rate coders, we attempt to provide a comprehensive survey by covering some of the traditional methodologies as well. We feel that this approach will not only point out key references but will also provide valuable background to the beginner. The paper starts with a historical perspective and continues with a brief discussion on the speech properties and performance measures. We then proceed with descriptions of waveform coders, sinusoidal transform coders, linear predictive vocoders, and analysis-by-synthesis linear predictive coders. Finally, we present concluding remarks followed by a discussion of opportunities for future research. >

Speech coding: a tutorial review

Providing voice and data communications to people away from their wireline telephones has become a major communication frontier. This frontier is being penetrated by evolving approaches to portable communications, e.g., cordless telephones, mobile radiotelephone, and radio paging. However, these approaches have many limitations; none can provide universal portable communications services. This paper discusses limitations of the evolving approaches and considers objectives and approaches for providing more universal digital portable communications as an integrated part of telephone exchange networks. These more universal communications could be accomplished by using demand-assigned radio links for the last thousand feet or so of telephone loops and sharing the remainder of the fixed distribution facilities. Fixed radio ports as integrated parts of telephone distribution networks could be placed throughout service regions. Efficient use of the radio spectrum could be insured by the planned reuse of radio frequencies throughout the regions. The severe multipath radio propagation environment within and around buildings that strongly influences the design of portable communications systems is described in the paper. System configurations and radio link techniques, that can provide reliable communications in the multipath environment, are discussed. Radio system calculations are illustrated for radio ports with 30-ft-high antennas in residential areas. The calculations indicate that radio link availability would be greater than 99 percent for 2000-ft port separations and 5-mW portable transmitters. Reuse of frequencies would require dividing the allocated frequency band into segments for use at adjacent ports. Calculations suggest that link availability in the cochannel interference environment would be greater than 99 percent, if 25 to 35 segments were used in residential areas.

Universal digital portable radio communications

Speaker recognition

We analyze the performance of a one-bit digital matched i t e r (DMF) responding to binary signaling through a noisy multipath channel. The output signal-to-noise ratio (SNR,) plays a key role in the analysis. The S N b performance is fully studied for a two-path channel, both fading and non-fading. For the general N-path channel, results are obtained only for the fading case. All results are conditioned on the knowledge of the time delays of all paths, and are valid only for smaIl input signal-to-noise ratio (SNRi). Most of the results have been verified by computer simulations.

M. Schroeder

Papers

Speech Coding

Correction to "Speech coding"