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.

Software simulation in GSM environment of Federal standard 1016 CELP vocoder

Abstract: The working performance of the Federal standard 1016 CELP (4.8 kbps) vocoder in GSM environment is discussed, and compared with that of the VSELP vocoder of standard GSM half-rate traffic channel. The conclusions through results analysis and comparison are helpful to propel the development of a low-bit-rate speech coder in the next generation digital mobile communication system.

Reducing the Codebook Search Time in G.728 Speech Coder Using Fuzzy ARTMAP Neural Networks

Abstract: Codebook search has high computational load in code excited linear prediction (CELP) speech coders. In this paper, a fuzzy ARTMAP neural network (FAMNN) is used to determine the best index of shape codebook in ITU-T G.728 speech coding algorithm. In this way, the gain value is calculated according to this index and the best index of gain codebook is determined based on the minimum distance to each of eight gain codebook values. Empirical results show that the proposed model leads to 50.7% reduction in codebook search time as compared to the traditional implementation of ITU-T G.728 encoder. However, the degradations in mean opinion score (MOS), perceived evaluation of speech quality (PESQ) and segmental signal to noise ratio (SNR ) are not significant, as well. seg

Low-complexity PARCOR coefficient quantization and prediction order estimation designed for entropy coding of prediction residuals

Abstract: This paper presents a set of low-complexity tools used in lossless coding of G.711 bitstream, based on linear prediction. One is an algorithm for quantizing the PARCOR/reflection coefficients and the other is an estimation method for the optimal prediction order. Both tools are based on a criterion that minimizes the entropy of the prediction residual signal and can be implemented in fixed-point arithmetic at very low-complexity. Since proposed methods show efficient performance in terms of compression and complexity, they are adopted in the Recommendation ITU-T G.711.0, a new standard for lossless compression of G.711 (A-law/ -law logarithmic PCM) payload.

Spectral Enhancement of Whispered Speech Based on Probability Mass Function

Abstract: Whispered speech can be effectively used for quiet and private communications over mobile phones and is also the communication means for ENT patients under a regime of voice rest. The reconstruction of natural sounding speech from such whispers can be useful for several types of application across different scientific fields ranging from communications to biomedical engineering. Despite the useful applications for a such technology, the reconstruction of natural speech from whispers has received relatively little research effort to date. This paper presents novel methods for spectral enhancement and formant smoothing with the aim of attaining more natural sounding speech within the reconstruction process. The proposed approach uses a probability mass-density function to identify a reliable formant trajectory through whispers and apply vocal modifications accordingly. Subjective evaluation experiments were performed, and are reported, to assess the performance of the techniques. A method for the near real-time conversion of whispers to normal phonated speech through a modified CELP codec has been discussed in our previously published work which, the proposed formant modification approach in this paper builds upon.

An application of the linear prediction technique to efficient coding of speech segments

Abstract: Summary form only given, as follows. The paper deals with the application of linear prediction technique to the speech synthesis of both italian and german languages by Standard Speech Reproducing Units (SSRU), it is by combining elementary speech segments of standardized charac teristics extracted fron utterances of native speakers. The nain feature of the method presented is the possibility of synthesizing in a higly intelligible form any nessage of such languages with a very limited amount of data. So far the use of linear predictive coding of the previously realized SSRU sets allowed a memory occupation less than 16 kb for the synthesis of italian language and less than 32 k-bytes for the combined synthesis of italian and german languages. The data flow rate is about 1 kb/s. A key property of the code with respect to methods previously used (i.e. simple concatenation of original segments ) relies in the possibility of greatly enhancing the naturalness of the synthesized speech by varying pitch, amplitude and duration of the synthetic segments. Further, the quantitative rules obtained for generating the SSRU's are expected to be useful, at least as a preliminary investigation tool, for synthesis-by-rule.