Topic
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.
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29 May 1991
TL;DR: A novel method of stochastic code book (SCB) searching for code excited linear predictive (CELP) coding is presented by implementing the counterpropagation neural network model to replace the exhaustive serial searching process by an open-loop, less computationally demanding code book parameters encoding.
Abstract: The authors present a novel method of stochastic code book (SCB) searching for code excited linear predictive (CELP) coding by implementing the counterpropagation neural network model The high performance of CELP is achieved at the expense of very high computational power required to find the SCB parameters The counterpropagation neural network model is used to replace the exhaustive serial searching process by an open-loop, less computationally demanding code book parameters encoding A scheme to embed the neural network model into the original CELP coding is presented The scheme is equivalent to a standard CELP with a 512 word SCB The system performance is analyzed and compared with the present closed-loop parameter searching method >
7 citations
01 Apr 1981
TL;DR: This paper discusses a form of non-linear prediction, namely, the prediction of the phase of speech signals, based upon a new treatment of the classical speech production model within a short-time analysis/synthesis framework.
Abstract: Prediction plays a key role in many signal processing applications. Linear Prediction has, in particular, been extremely useful to the development of digital speech processing techniques and applications. There is however a growing need for improved forms of prediction. We discuss, in this paper, a form of non-linear prediction, namely, the prediction of the phase of speech signals. This study is conducted within a short-time analysis/synthesis framework and is based upon a new treatment of the classical speech production model. Experimental data are presented confirming the theoretical results. Finally the use of phase prediction to low-bit rate, high-quality coding applications is discussed.
7 citations
TL;DR: A novel scalable speech coding scheme based on Compressive Sensing, which can operate at bit rates from 3.275 to 7.275 kbps is designed and implemented and offers the listening quality for reconstructed speech similar to that of Adaptive Multi rate - Narrowband codec at 6.7 kbps and Enhanced Voice Services (EVS) at 7.2 kbps.
7 citations
TL;DR: A new method is presented that offers efficient computation of Linear Prediction Coefficients (LPC) via a new Recursive Least Squares (RLS) adaptive filtering algorithm that is numerically robust, fast, parallelizable and has particularly good tracking properties.
7 citations
Patent•
03 Apr 2008TL;DR: In this paper, a layered code-excited linear prediction (CELP) encoder, an adaptive multirate wideband (AMR-WB), and methods of CELP encoding and decoding are presented.
Abstract: A layered code-excited linear prediction (CELP) encoder, an Adaptive Multirate Wideband (AMR-WB) encoder and methods of CELP encoding and decoding. In one embodiment, the encoder includes: (1) a core layer subencoder and (2) at least one enhancement layer subencoder, at least one of the core layer subencoder and the enhancement layer subencoder having first and second adaptive codebooks and configured to retrieve a pitch lag estimate from the second adaptive codebook and perform a closed-loop search of the first adaptive codebook based on the pitch lag estimate.
7 citations