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 text-to-speech system for Arabic using neural networks

Abstract: Text-to-speech synthesis is of great interest and its applications are several. For this reason, it has interested many researchers for decades. Two methods are usually used: synthesis by rule and synthesis by concatenation of pre-recorded sounds. But these methods have some disadvantages such as difficulty to be adapted to a new speaker or to a new language. Recently, neural networks (NN) have been used with nonconventional problems where a traditional solution seems impossible. Text-to-speech appears as one of these problems. In this field, it has been shown that NN don't work well when they are directly fed with speech samples. Therefore, works have been done to explore and evaluate different parametric forms of speech based on linear predictive coding (LPC), used for training, and found that LSP produced the best results. However, these methods don't take into account residual signal and speech produced was machine-like and not natural. We propose in this paper to drive the NN with codebook-excited linear prediction (CELP), which provides high quality speech, to perform Arabic speech synthesis.

Mobile audio-visual terminal: system design and subjective testing in DECT and UMTS networks

Abstract: It is anticipated that there will shortly be a requirement for multimedia terminals that operate via mobile communications systems. This paper presents a functional specification for such a terminal operating at 32 kb/s in a Digital European Cordless Telecommunications (DECT) and Universal Mobile Telecommunications System (UMTS) radio network. A terminal has been built, based on a PC with digital signal processor (DSP) boards for audio and video coding and decoding. Speech coding is by a phonetically driven code-excited linear prediction (CELP) speech coder and video coding by a block-oriented hybrid discrete cosine transform (DCT) coder. Separate channel coding is provided for the audio and video data. The paper describes the techniques used for audio and video coding, channel coding, and synchronization. Methods of subjective testing in a DECT network and in a UMTS network are also described. These consisted of subjective tests of first impressions of the mobile audio-visual terminal (MAVT) quality, interactive tests, and the completion of an exit questionnaire. The test results showed that the quality of the audio was sufficiently good for comprehension and the video was sufficiently good for following and repeating simple mechanical tasks. However, the quality of the MAVT was not good enough for general use where high-quality audio and video was needed, especially when transmission was in a noisy radio environment.

Techniques for improving the quality of LD-CELP coders at 8 kb/s

Abstract: The authors present an 8 kb/s low delay speech coder which is based on the code excited linear prediction (CELP) algorithm. They concentrate on analyzing the problem areas in backward predictive systems and solutions to alleviate these problems. The authors report on a forward linear predictive coding adaptive scheme to eliminate such distortions. Another approach is to use a windowing technique in the frequency domain on the error signal in analysis-by-synthesis procedures. The adaptation of the long term predictor (LTP) coefficients is also considered in a backward and forward mode for differential pitch coding of the LTP lags. The role of the excitation gain update rate is also examined in providing higher quality and better adaptation of the gains for an efficient vector quantization procedure. An 8-kb/s coder with a buffering delay of 4 ms has been informally subjectively tested, and the latest test results indicate a performance equal to that of the GSM at worst case. >

Steganography Approach of Weighted Speech Analysis with and without Vector Quantization using Variation in Weight Factor

Abstract: This Paper basically focuses on the analysis and synthesis of the speech signal which takes reference from the speech coding technique of Conjugate-Structure Algebraic Code Excited Linear Prediction (CS-ACELP) and also the concept of vector quantization. The proposed technique analyses the variation in weighted speech by the changes in the weight factor and also by implementing it with and without vector quantization. This algorithm is based on CELP coding technique which works on analysis by synthesis principle with the frame size of 80 samples (10 ms). Steganography is implemented in the LSB of the input cover speech which contributes to the high frequency component of the cover speech. The weighted speech signal is generated using both quantized and unquantized LP parameters, which is being tested on various grounds to basically observe and analyze its overall performance. At the end an analytic comparison between the original and the weighted speech signal both subjectively as well as objectively is done. The values of the two weight factors produce a considerable change in the weighted speech quality.