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.

Voice encoding device

Abstract: PURPOSE:To offer the voice encoding device provided with a pitch predictor whose amount of information is small, and also, can predict a signal of pitch length of a high frequency with high accuracy. CONSTITUTION:In a CELP voice encoding processing, transmission of pitch length information is executed by plural sub-frame units, and in order to execute a determination of pitch length, an input sound signal is predicted by a linear predictor 102 at every plural sub-frames, and a linear prediction residual signal is calculated. From a past exciting signal in an adaptive code book 104, and a linear prediction residual signal, pitch length is determined 121 by setting a mutual correlation coefficient as an evaluation reference. In the case of determining a pitch prediction coefficient, a pitch prediction 123 is executed to the whole code book 124 of the pitch prediction coefficient by the pitch length derived previously at every sub-frame, and a reproducing signal is subjected to auditory weighting, and thereafter, a coefficient by which an error to an input signal becomes minimum is selected.

An Inter-frame Correlation Based Error Concealment of Immittance Spectral Coefficients for Mobile Speech and Audio Codecs

Abstract: This paper proposes an inter-frame correlation based error concealment approach for hybrid CELP (Code Excited Linear Prediction) and transform codec's with both good speech and audio quality at moderate bit rates. The proposed scheme is designed to overcome the main challenge due to the diversified characteristics of input signals. The underlying idea is to employ the inter-frame correlation of previous neighborhood frames to circumvent the pitfalls of referring to the unrelated frames, and to enable effective prediction of ISF (Immittance Spectral Frequencies) spectrum coefficients of missing frames from the immediate relative history using linear regression approach. Objective and subjective evaluation results for the proposed approach, in comparison with existing technique of AVS-P10 (Audio Video coding of China Standard Part 10 -- Mobile Speech and Audio Codec), provide strong evidence for gains across a variety of speech and audio signals.

Quantization of Predictor Coefficients in Speech Coding

Abstract: The purpose of this thesis is to examine techniques of efficiently coding Linear Predictive Coding (LPC) coefficients with 20 to 30 bits per 20 ms speech frame. Scalar quantization is the first approach evaluated. In particular, experiments with LPC quantizers using reflection coefficients and Line Spectral Frequencies (LSF's) are presented. Results in this work show that LSF's require significantly fewer bits than reflection coefficients for comparable performance. The second approach investigated is the use of vector-scalar quantization. In the first stage, vector quantization is performed. The second stage consists of a bank of scalar quantizers which code the vector errors between the original LPC coefficients and the components of the vector of the quantized coefficients. The new approach in this work is to couple the vector and scalar quantization stages. Every codebook vector is compared to the original LPC coefficient vector to produce error vectors. The components of these error vectors are scalar quantized. The resulting vectors from the overall vector-scalar quantization are all compared to the input vector and the closest one selected. For practical implementations, methods of reducing the computational complexity are examined. The second innovation into vector-scalar quantization is the incorporation of a small adaptive codebook to the large fixed codebook. Frame-to-frame correlation of the LPC coefficients is exploited at no extra cost in bits. Simple methods of limiting the propagation of error inherent in this partially differential scheme are suggested. The results of this thesis show that the performance of the vector-scalar quant i zation with the use of the two new techniques introduced is better then that of the scalar coding techniques currently used in conventional LPC coders. The average spectral distortion is significantly reduced as is the number of outliers.

Implementation of 2400 bps MELP vocoder on TMS320C44

Abstract: The MELP algorithm was standardized by the USA Department of Defense in 1997. The MELP algorithm features less complexity than the CELP algorithm with comparable output speech quality at half 2.4 kbit/s. This paper presents an implementation of a 2.4 kbit/s mixed excitation linear prediction speech coder using the TMS320C44 digital signal processor. The emphasis is on exploiting the DSP platform.