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 packet identification based on celp compression parameters

Abstract: Mechanisms, and associated methods, for conducting voice analysis (e.g., speaker ID verification) directly from a compressed domain of a voice signal. Preferably, the feature vector is directly segmented, based on its corresponding physical meaning, from the compressed bit stream.

Synthesis of Codebooks with Perceptually Monitored Structure for Multiband CELP-Coders

Abstract: The work is devoted to subband decomposition scheme and training set composition effect on quality of reconstructed speech when synthesising codebooks for multiband CELP-coders. Codebooks quality and its dependence on the codebooks structure are studied. The research work presents multiband codebook with multistage organization and reconfigurable structure optimized by SNR, Bark Spectrum Distortion (BSD), Modified Bark Spectrum Distortion (MBSD) and Noise-to-Mask Ratio (NMR) criteria for control by psychoacoustic model on the base of Warped Discrete-Fourier Transform (WDFT).

Analytical Study of High Pitch Delay Resolution Technique for Tonal Speech Coding

Abstract: Problem statement: In tonal-language speech, since tone plays important role not only on the naturalness and also the intelligibility of the speech, it must be treated appropriately in a speech coder algorithm. Approach: This study proposes an analytical study of the technique of High Pitch Delay Resolutions (HPDR) applied to the adaptive codebook of core coder of Multi-Pulse based Code Excited Linear Predictive (MP-CELP) coder. Results: The experimental results show that the speech quality of the MP-CELP speech coder with HPDR technique is improved above the speech quality of the conventional coder. An optimum resolution of pitch delay is also presented. Conclusion: From the analytical study, it has been found that the proposed technique can improve the speech coding quality.

Excitation vector generator, speech coder, and speech decoder

Abstract: A noise vector reading section and a noise codebook of a conventional CELP type speech coding / decoding apparatus, which outputs different vector series depending on the value of the input seed oscillator and a plurality of seed parts of a seed storage which stores (seed of the oscillator), respectively It is replaced. Accordingly, it is not necessary to place the stored as a fixed vector in the fixed codebook (ROM) significantly reduce the memory capacity.

Non-linear encoding of the excitation source using neural networks for transition mode coding in CELP

Abstract: When a frame suffers erasure, the adaptive codebook at the decoder is no longer in sync with the one at the encoder. When the frame that is erased is a frame following the voice-onset frame, this loss of synchronization of the codebooks severely degrades the quality of the decoded speech. This degradation is primarily because no meaningful excitation signal is present in the adaptive codebook. In this paper, an autoassociative neural network (AANN) with a compression layer is used to capture the characteristics of the excitation source around the GCIs. A transition mode frame that differs from the conventional CELP frame without altering the bit-rate is proposed to deal with this problem of frame drops during transition regions. In this transition mode frames, the compressed representation of the excitation source around the GCIs obtained through AANNs is used to reconstruct the adaptive codebook at the receiver. It is shown that the proposed method improves the quality of the decoded speech.