Algorithm based on 2‐bit adaptive delta modulation and fractional linear prediction for Gaussian source coding

in IET Signal Processing (2021), 15(6), 410-423

A novel 2-bit adaptive delta modulation (ADM) algorithm is presented based on uniform scalar quantization and fractional linear prediction (FLP) for encoding the signals modelled by a Gaussian probability ... [more ▼]

A novel 2-bit adaptive delta modulation (ADM) algorithm is presented based on uniform scalar quantization and fractional linear prediction (FLP) for encoding the signals modelled by a Gaussian probability density function. The study focusses on two major areas: realization of a 2-bit adaptive quantizer based on Q-function approximation that significantly facilitates quantizer design; and implementation of a recently introduced FLP approach with the memory of two samples, which replaces the first-order linear prediction used in standard ADM algorithms and enables improved performance without increasing transmission costs. It furthermore represents the first implementation of FLP in signal encoding, therefore confirming its applicability in a real signal-processing scenario. Based on the performance analysis conducted on a real speech signal, the proposed ADM algorithm with FLP is demonstrated to outperform other 2-bit ADM baselines by a large margin for the gain in signal-to-noise ratio achieved over a wide dynamic range of input signals. The results of this research indicate that ADM with adaptive quantization based on Q-function approximation and adaptive FLP represents a promising solution for encoding/compression of correlated time-varying signals following the Gaussian distribution. [less ▲]

Gaussian source coding based on variance-mismatched three-level scalar quantisation using Q-function approximations

in IET Communications (2020), 14(4), 594-602

Novel Two-Bit Adaptive Delta Modulation Algorithms

in Informatica (2019), 30(1), 117-134

This paper introduces two novel algorithms for the 2-bit adaptive delta modulation, namely 2-bit hybrid adaptive delta modulation and 2-bit optimal adaptive delta modulation. In 2-bit hybrid adaptive ... [more ▼]

This paper introduces two novel algorithms for the 2-bit adaptive delta modulation, namely 2-bit hybrid adaptive delta modulation and 2-bit optimal adaptive delta modulation. In 2-bit hybrid adaptive delta modulation, the adaptation is performed both at the frame level and the sample level, where the estimated variance is used to determine the initial quantization step size. In the latter algorithm, the estimated variance is used to scale the quantizer codebook optimally designed assuming Laplace distribution of the input signal. The algorithms are tested using speech signal and compared to constant factor delta modulation, continuously variable slope delta modulation and instantaneously adaptive 2-bit delta modulation, showing that the proposed algorithms offer higher performance and significantly wider dynamic range. [less ▲]

An efficient two-digit adaptive delta modulation for Laplacian source coding

in International Journal of Electronics (2019), 106(7), 1085-1100

Delta Modulation (DM) is a simple waveform coding algorithm used mostly when timely data delivery is more important than the transmitted data quality. While the implementation of DM is fairly simple and ... [more ▼]

Delta Modulation (DM) is a simple waveform coding algorithm used mostly when timely data delivery is more important than the transmitted data quality. While the implementation of DM is fairly simple and inexpensive, it suffers from several limitations, such as slope overload and granular noise, which can be overcome using Adaptive Delta Modulation (ADM). This paper presents novel 2-digit ADM with six-level quantization using variable-length coding, for encoding the time-varying signals modelled by Laplacian distribution. Two variants of quantizer are employed, distortion-constrained quantizer which is optimally designed for minimal mean-squared error (MSE), and rate-constrained quantizer, which is suboptimal in the minimal MSE sense, but enables minimal loss in SQNR for the target bit rate. Experimental results using real speech signal are provided, indicating that the proposed configuration outperforms the baseline ADM algorithms, including Constant Factor Delta Modulation (CFDM), Continuously Variable Slope Delta Modulation (CVSDM), 2-digit and 2-bit ADM, and operates in a much wider dynamic range. [less ▲]

Forward Adaptive Laplacian Source Coding Based on Restricted Quantization

in Information Technology and Control (2018), 47(2), 209-219

A novel solution for Laplacian source coding based on three-level quantization is proposed in this paper. The restricted three-level quantizer is designed by assuming the restricted Laplacian distribution ... [more ▼]

A novel solution for Laplacian source coding based on three-level quantization is proposed in this paper. The restricted three-level quantizer is designed by assuming the restricted Laplacian distribution of the input signal. Quantizer and Huffman encoder are jointly designed. Forward adaptive scheme was employed, where the adaptation to the signal variance (power) was performed on frame-by frame basis. We employ switched model that consists of two restricted quantizers having unequal support regions. The simulation results (measured as SQNR) of the proposed scheme with a switched restricted three-level quantizer are compared to the cases when it involves three-level unrestricted quantizer and the Lloyd-Max quantizers having N=2 and N=4 levels. It is shown that the proposed solution offers performance comparable to the one of N=4 levels Lloyd-Max’s baseline with large savings in bit rate, while outperforming two other baselines. [less ▲]

Design of nonlinear predictors for adaptive predictive coding of speech signals

in Proceedings of the 21st Telecommunications Forum Telfor (TELFOR) (2013, November)

Linear predictive coding is probably the most frequently used technique in speech signal processing. Its main advantage comes from the analogy of the simplified vocal tract model with speech production ... [more ▼]

Linear predictive coding is probably the most frequently used technique in speech signal processing. Its main advantage comes from the analogy of the simplified vocal tract model with speech production system. However, this neglects nonlinearities in the speech production process. The paper deals with nonlinear prediction of speech based on truncated Volterra series. Long-term one-tap Volterra predictor is designed in order to decrease computational complexity. Further improvements are obtained using frame/subframe structure and fractional delay. [less ▲]

Low-Order Volterra Long-Term Predictors

in Proceedings of the 10. ITG Symposium on Speech Communication (2012, September)

Models based on linear prediction have been used for several decades in different areas of speech signal processing. While the linear approach has led to great advances in the last 40 years, it neglects ... [more ▼]

Models based on linear prediction have been used for several decades in different areas of speech signal processing. While the linear approach has led to great advances in the last 40 years, it neglects nonlinearities present in the speech production mechanism. This paper compares the results of long-term nonlinear prediction based on second-order and third-order Volterra filters. Additional improvement can be obtained using fractionaldelay long-term prediction. Experimental results reveal that the proposed method outperforms linear long-term prediction techniques in terms of prediction gain. [less ▲]

Switched adaptive quantiser for speech compression based on optimal companding and correlation

in IET Signal Processing (2011), 5(7), 701-707

This study describes a novel adaptive quantiser based on the optimal companding technique. Adaptation is achieved by adjusting the input of the fixed or non-adaptive quantiser according to the estimated ... [more ▼]

This study describes a novel adaptive quantiser based on the optimal companding technique. Adaptation is achieved by adjusting the input of the fixed or non-adaptive quantiser according to the estimated and quantised gain on each particular frame. In such a way better quantiser adaptation to the varying input statistics is provided. Selection of the appropriate bit rate is performed depending on the value of the correlation coefficient ρ on each frame. The decision thresholds for ρ are determined under the condition that the signal to quantisation noise ratio does not drop under 34.3ρdB, satisfying the G.712 standard quality of speech, while decreasing the bit rate. The information about the gain and about the chosen bit rate is then transferred as a side information to a decoder. Although this slightly increases the side information, the overall savings in the bit rate have shown to be substantial. Theoretical and experimental results are provided, which point out the benefits that can be achieved using the proposed algorithm. [less ▲]

DPCM with Forward Gain-Adaptive Quantizer and Simple Switched Predictor for High Quality Speech Signals

in Advances in Electrical and Computer Engineering (2010), 10(4), 95-98

In this article DPCM (Differential Pulse Code Modulation) speech coding scheme with a simple switched first order predictor is presented. Adaptation of the quantizer to the signal variance is performed ... [more ▼]

In this article DPCM (Differential Pulse Code Modulation) speech coding scheme with a simple switched first order predictor is presented. Adaptation of the quantizer to the signal variance is performed for each particular frame. Each frame is classified as high or low correlated, based on the value of the correlation coefficient, then the selection of the appropriate predictor coefficient and bitrate is performed. Low correlated frames are encoded with a higher bitrate, while high correlated frames are encoded with a lower bitrate without the objectionable loss in quality. Theoretical model and experimental results are provided for the proposed algorithm. [less ▲]