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 Perceptual Weighting Filter Loss for DNN Training in Speech Enhancement

Abstract: Single-channel speech enhancement with deep neural networks (DNNs) has shown promising performance and is thus intensively being studied. In this paper, instead of applying the mean squared error (MSE) as the loss function during DNN training for speech enhancement, we design a perceptual weighting filter loss motivated by the weighting filter as it is employed in analysis-by-synthesis speech coding, e.g., in code-excited linear prediction (CELP). The experimental results show that the proposed simple loss function improves the speech enhancement performance compared to a reference DNN with MSE loss in terms of perceptual quality and noise attenuation. The proposed loss function can be advantageously applied to an existing DNN-based speech enhancement system, without modification of the DNN topology for speech enhancement. The source code for the proposed approach is made available.

Advanced pre-and-post processing techniques for speech coding.

Abstract: Advances in digital technology in the last decade have motivated the development of very efficient and high quality speech compression algorithms. While in the early low bit rate coding systems, the main target was the production of intelligible speech at low bit rates, expansion of new applications such as mobile satellite systems increased the demand for reducing the transmission bandwidth and achieving higher speech quality. This resulted in the development of efficient parametric models for speech production system. These models were the basis of powerful speech compression algorithms such as CELP, MBE, MELP and WI. The performance of a speech coder not only depends on the speech production model employed but also on the accurate estimation of speech parameters. Periodicity, also known as pitch, is one of the speech parameters that greatly affect the synthesised speech quality. Thus, the subject of pitch determination has attracted much research in the area of low bit rate coding. In these studies it is assumed that for a short segment of speech, called frame, the pitch is fixed or smoothly evolving. The pitch estimation algorithms generally fail to determine irregular variations, which can occur at onset and offset speech segments. In order to overcome this problem, a novel preprocessing method, which detects irregular pitch variations and modifies the speech signal such as to improve the accuracy of the pitch estimation, is proposed. This method results in more regular speech while maintaining perceptual speech quality. The perceptual quality of the synthesised speech may also be improved using postfiltering techniques. Conventional postfiltering methods generally consider the enhancement of the whole speech spectrum. This may result in the broadening of the first formant, which leads to the increase of quantisation noise for this formant. A new postfiltering technique, which is based on factorising the linear prediction synthesis filter, is proposed. This provides more control over the formant bandwidth and attenuation of spectral speech valleys. Key words: Pitch smoothing, speech pre-processor, postfiltering.

Hybrid audio coding for speech and audio below medium bit rate

Abstract: A novel a audio/speech coding algorithm, hybrid audio coding (HAC) is described. New features of the algorithm include window switching with generalized MDCT, an improved quantization scheme of the MDCT coefficients, and waveform normalization in the time domain. HAC provides a good quality at a bit rate of 8 to 16 kbps, and it is also proven that the developed algorithm is effective for both audio and speech signals.

Linear prediction of audio signals

Abstract: Linear prediction (LP) is a valuable tool for speech analysis and coding, due to the efficiency of the autoregressive model for speech signals. In audio analysis and coding, the sinusoidal model is much more popular, which is partly due to the poor performance of audio LP. By examining audio LP from a spectral estimation point of view, we observe that the distribution of the audio signal’s dominant frequencies in the Nyquist interval is a critical factor determining LP performance. In this framework, we describe five existing alternative LP methods and illustrate how they all attempt to solve the observed frequency distribution problem.

Variable rate techniques for CELP speech coding

Abstract: The development of variable-rate speech coding techniques has recently become an area of significant research interest, and several variable-rate schemes have been discussed in the literature. Here, we discuss general techniques for efficient variable-rate coding and the analysis cues from which these coding modes are derived. These techniques include fixed-update, variable-allocation and variable-update, fixed-allocation approaches to formant and pitch filter encoding. Since code-excited linear prediction (CELP) is popular for communications quality speech coding below 8 kbps, we provide simulation results for the several techniques in the context of variable-rate CELP coders with average encoded rate below 2 kbps.