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.

On a time reduction of pitch searching by the regular pulse search technique in the CELP vocoder

Abstract: Code excited linear prediction (CELP) speech coders exhibit good performance at data rates as low as 4800 bps. The major drawback of CELP type coders is the large amount of computational time. In this paper, we propose a new pitch codebook search method that restricts some range of the pitch searching by using the regular pulse excitation (RPE) searching technique. Applying the proposed method to the 8 kbps CELP vocoder, we can get approximately 48% complexity reduction in the pitch search.

A 2.4 kbps variable bit rate ADP-CELP speech coder

Abstract: This paper presents a variable bit rate ADP-CELP (adaptive density pulse code excited linear prediction) coder that selects one of four kinds of coding structure in each frame based on short time speech characteristics. To improve speech quality and reduce the average bit rate, we have developed a speech/non-speech classification method using spectrum envelope variation, which is robust for background noise. In addition, we propose an efficient pitch lag coding technique. The technique interpolates consecutive frame pitch lags and quantizes a vector of relative pitch lags consisting of variation between an estimated pitch lag and a target pitch lag in plural subframes. The average bit rate of the proposed coder was approximately 2.4 kbps for speech sources with activity factor of 60%. Our subjective testing indicates the quality of the proposed coder exceeds that of the Japanese digital cellular standard with rate of 3.45 kbps.

Low bit rate coding for speech and audio using mel linear predictive coding (MLPC) analysis.

Abstract: This paper proposes a low bit rate coding method for speech and audio using a new analysis method named MLPC (Mel-LPC analysis). In the MLPC analysis method a spectrum envelope is estimated on a melor bark-frequency scale, so as to improve the spectral resolution in the low frequency band. This analysis is accomplished with about two-fold increase in computation over the standard LPC analysis. Our coding algorithm using the MLPC analysis consists of five key parts: time frequency transformation, inverse filtering by the MLPC spectrum envelope, power normalization, perceptual weighting estimation, and the multi-stage vector quantization. In subjective experiments, we have investigated the performance of MLPC analysis method, through the evaluation of paired comparison tests between the MLPC analysis and the standard LPC one in inverse filtering. In all bit rates, almost all the listeners feel decoding signals by the MLPC analysis method is superior to the LPC one. Especially in low bit rate, there is a great difference between them.

Basic algorithm of conjugate-structure algebraic CELP (CS-ACELP) speech coder

Abstract: The ITU-T approved the Conjugate-Structure Algebraic CELP (CS-ACELP) speech coder that will be used for Future Public Land Mobile Telecommunication Systems (FPLMTS) at its November 1995 meeting.This paper gives an overview of CS-ACELP and describes the algebraic codebook*, perceptual weighting, and quantization methods for LSP parameters and gain. It also discusses implementation aspects. Subjective testing indicates that the quality of this coder is equivalent to that of 32-kbit/s Adaptive Differential Pulse Code Modulation.

Comparison of ARMA modelling methods for low bit rate speech coding

Abstract: There are two main parts of parametric speech coding algorithms such as codebook-excited linear prediction (CELP): the determination of the vocal tract filter parameters and the selection of the excitation signals based on a perceptual error criterion. The vocal tract includes the oral and nasal cavities depending on the type of speech segments (e.g. nasals and unvoiced fricatives). The contribution from the nasal tract suggests the need for an ARMA (or pole-zero) model instead of the conventional AR (pole only) model. The paper compares the performance of several ARMA modelling techniques in estimating the vocal tract filter parameters. The best method in terms of spectral fit and computational complexity is then applied to a CELP-type speech coding algorithm, with results which are superior to conventional AR models. >