Code-excited linear prediction

About: Code-excited linear prediction is a research topic. Over the lifetime, 2025 publications have been published within this topic receiving 28633 citations. The topic is also known as: CELP.

A joint source-channel speech coder using hybrid digital-analog (HDA) modulation

Abstract: A joint source-channel coding system for transmitting speech on a bandlimited additive white Gaussian noise (AWGN) channel is presented. The proposed method uses a hybrid of digital and analog modulation techniques. The digital part of the system consists of a Federal Standard 1016 code-excited linear predictive (FS 1016 CELP) speech coder followed by a rate-3/5 parallel concatenated (turbo) error correcting code. The analog part, which transmits the quantization error due to the FS 1016 CELP coder, consists of a linear encoder and decoder. The advantage of the proposed system is that it achieves excellent rate-distortion/capacity performance that is common in digital systems while maintaining a "graceful degradation" characteristic that is common in analog systems. Comparisons are made with three purely digital systems and an analog system-with all systems operating at the same overall rate. A formal listening test shows that, at high channel SNR, the improved performance of the proposed hybrid system (versus the purely digital systems) is noticeable to the average listener. Finally, an informal listening test indicates that at low channel SNR (where the error correcting code breaks down) the decoded speech of the hybrid system is still intelligible.

Fractal excitation signals for CELP speech coders

Abstract: A class of random signals is presented as a new excitation codebook for stochastic predictive speech coders. These signals, known as fractional noises, depend on a single parameter, 0

A packet loss concealment algorithm based on time-scale modification for CELP-type speech coders

Abstract: We propose a packet loss concealment algorithm for a code-excited linear prediction (CELP) speech coder. We perform a time-scale modification (TSM) using a waveform similarity overlap-add (WSOLA) technique to reconstruct the excitation signal of the lost or dropped frames. In addition, when a lost frame is classified as a voiced, an adaptive codebook gain and a fixed codebook gain are estimated by a modified gain parameter re-estimation (GRE) technique. By applying these techniques, we can reduce quality degradation of the decoded speech and error propagation effect through the adaptive codebook memory. We apply the proposed scheme to the ITU-T G.729 standard speech coder to evaluate the performance of the proposed method. The perceptual evaluation of speech quality (PESQ) and AB preference tests under various packet loss conditions verify that the proposed algorithm is superior to the concealment algorithm embedded in the G.729.

A fast pitch searching algorithm using correlation characteristics in CELP vocoder

Abstract: The major drawback in the code excited linear prediction (CELP) type vocoders is their large computational requirements. In the present paper a simple method is proposed to reduce the pitch searching time in the pitch filter almost without degradation of quality. Based upon the observational regularity of the correlation function of speech, the searching range can be restricted to the positive side in pitch search. This is done by skipping the negative side with the width which is estimated from the previous positive envelope. In addition to that, the maximum number of available lags can be limited by the threshold, LT, which is set on 58 empirically. So, only the limited numbers of lags are considered in pitch search, which is less than a half of that of the full search method. By using the proposed method in pitch search, its required computations are greatly reduced. Experimental results show 51% time reduction almost without lowering the speech quality in segmental SNR measures. >

Speech compression using linear predictive coding(lpc)

Abstract: One of the most powerful speech analysis techniques is the method of linear predictive analysis This method has become the predominant technique for representing speech for low bit rate transmission or storage The importance of this method lies both in its ability to provide extremely accurate estimates of the speech parameters and in its relative speed of computation The basic idea behind linear predictive analysis is that the speech sample can be approximated as a linear combination of past samples The linear predictor model provides a robust, reliable and accurate method for estimating parameters that characterize the linear, time varying system In this project, we implement a voice excited