Showing papers on "Code-excited linear prediction published in 1982"

Predictive Coding of Speech at Low Bit Rates

Abstract: Predictive coding is a promising approach for speech coding. In this paper, we review the recent work on adaptive predictive coding of speech signals, with particular emphasis on achieving high speech quality at low bit rates (less than 10 kbits/s). Efficient prediction of the redundant structure in speech signals is obviously important for proper functioning of a predictive coder. It is equally important to ensure that the distortion in the coded speech signal be perceptually small. The subjective loudness of quantization noise depends both on the short-time spectrum of the noise and its relation to the short-time spectrum of the Speech signal. The noise in the formant regions is partially masked by the speech signal itself. This masking of quantization noise by speech signal allows one to use low bit rates while maintaining high speech quality. This paper will present generalizations of predictive coding for minimizing subjective distortion in the reconstructed speech signal at the receiver. The quantizer in predictive coders quantizes its input on a sample-by-sample basis. Such sample-by-sample (instantaneous) quantization creates difficulty in realizing an arbitrary noise spectrum, particularly at low bit rates. We will describe a new class of speech coders in this paper which could be considered to be a generalization of the predictive coder. These new coders not only allow one to realize the precise optimum noise spectrum which is crucial to achieving very low bit rates, but also represent the important first step in bridging the gap between waveform coders and vocoders without suffering from their limitations.

Harmonic coding: A low bit-rate, good-quality speech coding technique

Abstract: Low bit-rate, good-quality speech coding is one of the fundamental goals of today's speech processing research. Present-day coding techniques, like APC and ATC, are able to achieve good-quality transmission only down to about 12 kb/s. Below this rate, their quality degrades rapidly. On the other hand, the various kinds of vocoders, which operate up to about 5 kb/s, have inherent quality limitations which cannot be overcome by an increase of the bit rate. In this paper, a new coding scheme is presented, which is based on a recently developed spectral model for nonstationary voiced speech, and it forms the basis of a waveform coder and a vocoder which are introduced in this paper, and which share the same basic structure. Experimental results are presented, which show that both systems yield significant bit-rate reductions relative to present-day schemes of equivalent quality.

Speech analysis by selective linear prediction in the time domain

Abstract: Linear prediction method is one of the most frequently used analysis methods of speech. Covariance method and auto-correlation method of linear prediction often fail to make a precise analysis of speech because of the excitation source or fundamental frequency. In order to decrease the affect of the excitation source, various kinds of difference operations are usually employed for preprocessing. However, such preprocessings do not always work satisfactorily. Here proposed is a new approach to LPC analysis based on selective use of speech data to reject the data disturbed by the excitation source, and is called selective linear prediction method. The method is constructed aiming to improve the accuracy of analysis. First, the formulation of linear prediction is presented using generalized inverse matrices. Then, a successive computation is described based on Givens' reduction. The selective computation, which plays an essential role in our method, owes its efficiency to Givens' reduction. Finally the advantage of the proposed method is demonstrated by computer simulation using both synthetic and natural speech.

On spectral flattening techniques in residual-excited linear prediction vocoding

Abstract: Residual excited linear prediction (RELP) vocoder is considered to be a promising approach to medium rate (4.8 to 9.6 kbits/s) vocoding that does not require pitch extraction. One critical part of the RELP vocoder that affects greatly the synthetic speech quality is the spectral flattener in which high frequency components are regenerated from the baseband residual signal. In this paper several spectral flattening techniques so far proposed are first reviewed, and their advantages and disadvantages are discussed. Then, two improved methods are proposed. Those are the hybrid method and the split-band coding method. These new methods yield excellent synthetic speech quality when the transmission rate is 8 kbits/s.

Voice coding at 800 BPS and lower data rates with LPC vector quantization

Abstract: Design of an 800 bps LPC vocoder based on vector quantization is presented. Subjective evaluation under different channel error and acoustic-ambient noise conditions are discussed. The results indicate that it preserves much of the intelligibility as well as robustness of LPC. Further reduction in bit rate is achieved by eliminating frame to frame redundancy in the vocoder parameters. Techniques include frame repeat coding and the newly developed matrix coding technique.

Some experiments in ADPCM coding of images

Abstract: This paper is a preliminary report on a study of the application of two-dimensional linear prediction in image quantization. The study has focused on three major concerns: implementation of an adaptive linear predictor, adaptive quantization of the prediction error signal, and the adaptive predictive coding of density (logarithm of intensity) images. The results of the study indicate that through the use of adaptive prediction and quantization, a high level of image fidelity can be obtained for both intensity and density images at information rates well below one bit/pixel.