Immittance Spectral Frequency Research Articles

An Upgraded Version of the Binary Search Space-Structured VQ Search Algorithm for AMR-WB Codec

Adaptive multi-rate wideband (AMR-WB) speech codecs have been widely used for high speech quality in modern mobile communication systems, e.g., handheld mobile devices. Nevertheless, a major handicap is that a remarkable computational load is required in the vector quantization (VQ) of immittance spectral frequency (ISF) coefficients of an AMR-WB coding. In view of this, a two-stage search algorithm is presented in this paper as an efficient way to reduce the computational complexity of ISF quantization in AMR-WB coding. At stage 1, an input vector is assigned to a search subspace in an efficient manner using the binary search space-structured VQ (BSS-VQ) algorithm, and a codebook search is performed over the subspace at stage 2 using the iterative triangular inequality elimination (ITIE) approach. Through the use of the codeword rejection mechanisms equipped in both stages, the computational load can be remarkably reduced. As compared with the original version of the BSS-VQ algorithm, the upgraded version provides a computational load reduction of up to 51%. Furthermore, this work is expected to satisfy the energy saving requirement when implemented on an AMR-WB codec of mobile devices.

A Search Complexity Improvement of Vector Quantization to Immittance Spectral Frequency Coefficients in AMR-WB Speech Codec

An adaptive multi-rate wideband (AMR-WB) code is a speech codec developed on the basis of an algebraic code-excited linear-prediction (ACELP) coding technique, and has a double advantage of low bit rates and high speech quality. This coding technique is widely used in modern mobile communication systems for a high speech quality in handheld devices. However, a major disadvantage is that a vector quantization (VQ) of immittance spectral frequency (ISF) coefficients occupies a significant computational load in the AMR-WB encoder. Hence, this paper presents a triangular inequality elimination (TIE) algorithm combined with a dynamic mechanism and an intersection mechanism, abbreviated as the DI-TIE algorithm, to remarkably improve the complexity of ISF coefficient quantization in the AMR-WB speech codec. Both mechanisms are designed in a way that recursively enhances the performance of the TIE algorithm. At the end of this work, this proposal is experimentally validated as a superior search algorithm relative to a conventional TIE, a multiple TIE (MTIE), and an equal-average equal-variance equal-norm nearest neighbor search (EEENNS) approach. With a full search algorithm as a benchmark for search load comparison, this work provides a search load reduction above 77%, a figure far beyond 36% in the TIE, 49% in the MTIE, and 68% in the EEENNS approach.

An efficient search algorithm for ISF vector quantization in AMR‐WB speech codec

The adaptive multi‐rate wideband (AMR‐WB) speech codec with a sampling rate of 16 kHz is one of the speech codecs applied to 4G mobile communication systems as a way to remarkably improve the speech quality of a smartphone. However, a major drawback is that the vector quantization of the immittance spectral frequency (ISF) coefficients takes up the second largest of the total computational load of the AMR‐WB encoder. In other words, the speech quality is improved at the cost of high battery power consumption. Accordingly, this letter presents a triangular inequality elimination algorithm equipped with a dynamic and an intersection mechanism, named DI‐TIE, as a means to considerably improve the performance of ISF coefficient quantization in AMR‐WB speech codec. Both mechanisms are designed in a way that recursively enhances the performance of TIE algorithm. This proposal is demonstrated by experimental results as a superior search algorithm relative to a conventional TIE and a multiple TIE (MTIE) approaches. With a full search algorithm as a benchmark for search load comparison, this work provides a search load reduction of more than 77%, a figure far beyond the 36% in the TIE and 49% in the MTIE approach. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Skew Gaussian mixture models for speaker recognition

Gaussian mixture models (GMMs) are widely used in speech and speaker recognition. This study explores the idea that a mixture of skew Gaussians might capture better feature vectors that tend to have skew empirical distributions. It begins with deriving an expectation maximisation (EM) algorithm to train a mixture of two-piece skew Gaussians that turns out to be not much more complicated than the usual EM algorithm used to train symmetric GMMs. Next, the algorithm is used to compare skew and symmetric GMMs in some simple speaker recognition experiments that use Mel frequency cepstral coefficients (MFCC) and line spectral frequencies (LSF) as the feature vectors. MFCC are one of the most popular feature vectors in speech and speaker recognition applications. LSF were chosen because they exhibit significantly more skewed distribution than MFCC and because they are widely used [together with the related immittance spectral frequencies (ISF)] in speech transmission standards. In the reported experiments, models with skew Gaussians performed better than models with symmetric Gaussians and skew GMMs with LSF compared favourably with both skew symmetric and symmetric GMMs that used MFCC.

Robust coding of wideband speech immittance spectral frequencies

In this paper, we propose a reduced complexity stochastic joint source-channel coding system developed for efficient and robust coding of wideband speech ISF (Immittance Spectral Frequency) parameters. Initially, the aim of this encoding system was to achieve a transparent quantization of ISF parameters for ideal transmissions over a noiseless channels. It was designed based on the switched split vector quantization (SSVQ) technique and called “ISF-SSVQ coder”. After that, our interest was drawn to the improvement of the ISF-SSVQ robustness for transmissions over a noisy channel. To protect implicitly our ISF coders, we developed a stochastic joint source-channel coding system based on a reduced complexity version of the channel optimized SSVQ technique. Simulation results will show that our new encoding system, called ISF-SCOSSVQ coder, can provide a good implicit protection to ISF parameters. The ISF-SCOSSVQ coder was further used to encode the ISF parameters of the Adaptive Multi-rate Wideband (AMR-WB, ITU-T G.722.2) speech coder operating over a noisy channel. We will show that the proposed ISF-SCOSSVQ coder contribute significantly in the improvement of the AMR-WB performance by ensuring a good coding robustness of its ISF parameters.

Interpolative frame-erasure concealment of moving-average prediction coding parameters in ITU-T Recommendation G.718

An interpolative concealment algorithm for parameters encoded using interframe prediction is presented. A lost parameter is concealed using information received correctly in the next frame. In the presented algorithm, a lost parameter is determined by minimising the sum of distances between the parameters decoded in the previous and current frames and the parameters decoded in the current and subsequent frames. The algorithm was applied to concealment algorithms for the immittance spectral frequency and fixed codebook gain parameters of the ITU-T Recommendation G.722.2 decoder. The effectiveness of the algorithm was confirmed in a random frame erasure condition. The algorithm was adopted as a part of the G.722.2-interoperable mode of the new ITU-T Recommendation G.718 approved in June 2008.

Computation of Immittance and Line Spectral Frequencies Based on Inter-frame Ordering Property

Line spectral frequencies (LSF) and immittance spectral frequencies (ISF) are widely used in modern speech codecs based on autoregressive model. This paper addresses LSF and ISF calculation problems. The investigation of LSF/ISF placement on adjacent quasi-stationary frames is performed. It is shown that in majority of cases the inter-frame ordering property takes place. On this basis a new approach to LSF/ISF calculation is proposed. It is shown that LSF/ISF localization task is mainly reduced to verification of inter-frame ordering property. The computational expenses are reduced in 3.4 times in comparison with widely used Kabal’s method. Besides, the maximum number of operations is lower than the minimum expenses of accelerated Kabal’s method. The method is implemented on fixed-point DSP and showed stable performance.