AMR-WB Research Articles

Optimized Multirate Wideband Speech Steganography for Improving Embedding Capacity Compared with Neighbor-Index-Division Codebook Division Algorithm

Aim: The main motive of this study is to perform Adaptive Multi Rate Wideband (AMR-WB) Speech Steganography in network security to produce the stego speech with less loss of quality while increasing embedding capacities. Materials and Methods: TIMIT Acoustic-Phonetic Continuous Speech Corpus dataset consists of about 16000 speech samples out of which 1000 samples are taken and 80% pretest power for analyzing the speech steganography. AMR-WB Speech steganography is performed by Diameter Neighbor codebook partition algorithm (Group 1) and Neighbor Index Division codebook division algorithm (Group 2). Results: The AMR-WB speech steganography using DN codebook partition obtained average quality rate of 2.8893 and NID codebook division algorithm obtained average quality rate of 2.4196 in the range of 300bps embedding capacity. Conclusion: The outcomes of this study proves that the decrease in quality in NID is twice more than the DN based steganography while increasing the embedding capacities.

VoLTE cell capacity estimation using AMR‐WB codecs and considering VAF, SID, packet bundling, and TTI bundling

SummaryThe Voice over Long‐Term Evolution (VoLTE) cell capacity notably has an influence on Call Admission Control (CAC) in Long‐Term Evolution (LTE) network. In literature, many techniques have been studied to estimate the LTE cell capacity, but most of them are throughput‐based physical layer (PHY layer) estimate. These estimates do not consider delay requirement, transmission loss, and protocol overhead. In this paper, we have proposed novel analytical models for estimating the VoLTE cell capacity in terms of number of users by considering available physical resource blocks (PRBs) in each bandwidth, voice traffic‐based characteristics such as voice activity factor (VAF), silent insertion descriptor (SID), and radio‐specific techniques such as packet bundling and transmission time interval (TTI) bundling. Our developed analytical models are then used to investigate the effect of modulation and coding scheme (MCS) and Adaptive Multi‐RateWideband (AMR‐WB) voice codec on VoLTE cell capacity. Results show that higher order modulation scheme with lower bit voice codec accommodates maximum number of VoLTE users. Further, the impact of VAF, SID, packet bundling, and TTI bundling on VoLTE cell capacity is investigated in different radio conditions. Finally, using our proposed model, the effect of hybrid automatic repeat request (HARQ) retransmission on VoLTE cell capacity is investigated.

Convolutional Neural Networks to Enhance Coded Speech

Enhancing coded speech suffering from far-end acoustic background noise, quantization noise, and potentially transmission errors, is a challenging task. In this work we propose two postprocessing approaches applying convolutional neural networks (CNNs) either in the time domain or the cepstral domain to enhance the coded speech without any modification of the codecs. The time domain approach follows an end-to-end fashion, while the cepstral domain approach uses analysis-synthesis with cepstral domain features. The proposed postprocessors in both domains are evaluated for various narrowband and wideband speech codecs in a wide range of conditions. The proposed postprocessor improves speech quality (PESQ) by up to 0.25 MOS-LQO points for G.711, 0.30 points for G.726, 0.82 points for G.722, and 0.26 points for adaptive multirate wideband codec (AMR-WB). In a subjective CCR listening test, the proposed postprocessor on G.711-coded speech exceeds the speech quality of an ITU-T-standardized postfilter by 0.36 CMOS points, and obtains a clear preference of 1.77 CMOS points compared to legacy G.711, even better than uncoded speech with statistical significance. The source code for the cepstral domain approach to enhance G.711-coded speech is made available.

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.

Steganography algorithm for adaptive multi-rate wideband speech based on algebraic codebook search

Steganography algorithm for adaptive multi-rate wideband speech based on algebraic codebook search

A Novel AMR-WB Speech Steganography Based on Diameter-Neighbor Codebook Partition

Steganography is a means of covert communication without revealing the occurrence and the real purpose of communication. The adaptive multirate wideband (AMR-WB) is a widely adapted format in mobile handsets and is also the recommended speech codec for VoLTE. In this paper, a novel AMR-WB speech steganography is proposed based on diameter-neighbor codebook partition algorithm. Different embedding capacity may be achieved by adjusting the iterative parameters during codebook division. The experimental results prove that the presented AMR-WB steganography may provide higher and flexible embedding capacity without inducing perceptible distortion compared with the state-of-the-art methods. With 48 iterations of cluster merging, twice the embedding capacity of complementary-neighbor-vertices-based embedding method may be obtained with a decrease of only around 2% in speech quality and much the same undetectability. Moreover, both the quality of stego speech and the security regarding statistical steganalysis are better than the recent speech steganography based on neighbor-index-division codebook partition.

An Efficient VQ Codebook Search Algorithm Applied to AMR-WB Speech Coding

The adaptive multi-rate wideband (AMR-WB) speech codec is widely used in modern mobile communication systems for high speech quality in handheld devices. Nonetheless, a major disadvantage is that vector quantization (VQ) of immittance spectral frequency (ISF) coefficients takes a considerable computational load in the AMR-WB coding. Accordingly, a binary search space-structured VQ (BSS-VQ) algorithm is adopted to efficiently reduce the complexity of ISF quantization in AMR-WB. This search algorithm is done through a fast locating technique combined with lookup tables, such that an input vector is efficiently assigned to a subspace where relatively few codeword searches are required to be executed. In terms of overall search performance, this work is experimentally validated as a superior search algorithm relative to a multiple triangular inequality elimination (MTIE), a TIE with dynamic and intersection mechanisms (DI-TIE), and an equal-average equal-variance equal-norm nearest neighbor search (EEENNS) approach. With a full search algorithm as a benchmark for overall search load comparison, this work provides an 87% search load reduction at a threshold of quantization accuracy of 0.96, a figure far beyond 55% in the MTIE, 76% in the EEENNS approach, and 83% in the DI-TIE approach.

A Comparative Study of Voice Quality and Coverage for Voice over Long Term Evolution Calls Using Different Codec Mode-sets

In this paper, we examine the impact of four voice over long term evolution adaptive multi-rate wideband codec mode-sets on coverage at pedestrian and vehicular speeds. Industry-standardized mean opinion scores were used as a metric for voice quality. Controlled laboratory experiments simulating pedestrian speeds indicated that there was an improvement in voice quality when mode-set eight was employed. At vehicular speeds, mode-set eight outperformed the other mode-sets for path losses less than 130 dB; however, all four mode-sets experienced a significant decline in voice quality when the path loss was greater than 130 dB. Based on the current implementations, there are no significant benefits to lowering the mode-sets or deploying dynamic codec rate adaptation.

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.

A New Non-intrusive Model for Measuring VoLTE Quality based on Wideband E-model

Long Term Evolution (LTE) was initially designed for a high data rates network. However, voice service is always a main service that brings a big benefit for mobile operators. Hence the deployment of Voice over LTE (VoLTE) is very essential and urgent. LTE network is a fully All-IP network, thus, the deployment of VoLTE is very complex, specially for guaranteeing of Quality of Service (QoS) to meet quality of experience of mobile users. The key purpose of this paper is to present an object, non-intrusive prediction model for VoLTE quality based on LTE-Sim framework and Wideband (WB) E-model. In order to simulate the experiment, we deployed LTE-Sim framework combining C programming in Matlab software. The outputs of the LTE-Sim will be the inputs of the WB E-model. The output of the WB E-model is user satisfaction via Mean Opinion Score (MOS). In addition, due to voice over LTE network (VoLTE) uses Adaptive Multi-Rate Wideband (AMR-WB) for vocoder while LTE-Sim supports only G.729 codec for narrow band, thus, we propose to add AMR-WB codec into LTE-Sim software. The simulation results show that the proposed model can predict voice quality in LTE network via the WB E-model. The proposed model does not refer to the original signal, thus, it is very suitable for predicting voice quality in LTE network for many different scenarios which are configured in the LTE-Sim framework. The proposed model is very suitable for predicting VoLTE quality for transmission planning, and for researchers in Laboratory.

A novel frame error concealment scheme based on gain control for TCX audio codec

A novel frame error concealment scheme is proposed to improve the decoded audio quality of the receiver for transform coded excitation (TCX) audio codec. This scheme, which is a gain control approach based on the stability of linear predictive coding (LPC) filter, predicts the lost frames by utilizing the linear spectrum frequency and different continuous attenuation factor of different kinds of lost frames. Signal noise ratio (SNR) test and multiple stimuli with hidden reference and anchor (MUSHRA) test are conducted to evaluate the performance of this approach in adaptive multi-rate wideband plus (AMR-WB+) audio codec. Compared with the original frame error concealment scheme, our scheme achieves better audio recovery quality in AMR-WB+ audio codec.

Packet Loss Concealment Based on Deep Neural Networks for Digital Speech Transmission

In this paper, we propose the regression-based packet loss concealment (PLC) for digital speech transmission by using deep neural networks (DNNs) with a multiple-layer deep architecture. For the DNN training, log-power spectra and phases are employed as features in the input layer for the large training set, which ensures non-linear mapping the frames from the last correctly received frame to the missing frame. Once the training is accomplished by the restricted Boltzmann machine (RBM)-based pre-training to initialize the DNN, minimum mean square error (MMSE)-based fine tuning is then performed based on the back-propagation algorithm. In the reconstruction stage, the trained DNN model is fed with the features of the previous frames in order to estimate the log-power spectra and phases of the missing frames. Reconstruction is further improved by using the cross-fading technique to mitigate discontinuity between the reconstruction signal and good frame signal in the time-domain. To demonstrate the performance of the proposed algorithm, hidden Markov model (HMM)-based PLC algorithm and the PLC algorithm standardized in adaptive multi-rate wideband (AMR-WB) Appendix I were used for comparison. The experimental results show that the proposed approach provides better speech quality and speech recognition accuracy than the conventional approaches.

Resolution Warped Spectral Representation for Low-Delay and Low-Bit-Rate Audio Coder

We have devised a high-quality frequency-domain audio coder based on the state-of-the-art monaural wide-band coder aiming at its use in low-delay and low-bit-rate conditions. The coder efficiently represents frequency spectral envelopes of the target signals with low computational complexity using optimally prepared non-negative sparse matrices. The experimental results reveal that this representation has positive effects on the objective and subjective quality of the coder resulting in the comparable quality to the same bit rate of 3GPP Extended Adaptive Multi-Rate WideBand ( AMR-WB+), a coder which permits more than four times longer delay compared with the proposed coder. Consequently, this coder is suitable for applications in mobile communications, which require low delay and low complexity.

Effect of Speech Compression on the Automatic Recognition of Emotions

This paper investigates the effects of standard speech compression techniques on the accuracy of automatic emotion recognition. Effects of Adaptive Multi-Rates (AMR), Adaptive Multi-Rate Wideband (AMR-WB) and Extended Adaptive Multi-Rate Wideband (AMR-WB+) speech codecs were compared against emotion recognition from uncompressed speech. The recognition methods included techniques based on three different types of acoustic speech parameters: Teage Energy Operator features (TEO), Mel Frequency Cepstral Coefficients (MFCCs), and Glottal Time and Frequency domain features (GP-T and GP-F). The results showed that in general, all three speech compression techniques resulted in the reduction of emotion recognition accuracy. However, the amount of degradation varied across compression methods and types of acoustic features. It was observed that the accuracy of emotion recognition using the AMR-WB technique was higher than the accuracy of the AMR-WB+ and the AMR codecs. Further, the TEO-PWP features showed much more robust performance under different compression rates than the MFCC, GP-T and GP-F features.

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.

Modification of codebook search in adaptive multi-rate wideband speech codecs using intelligent optimization algorithms

In recognition of high-quality wideband speech codecs, several standardization activities have been conducted, resulting in the selection of a wideband speech codec called adaptive multi-rate wideband (AMR-WB). The algebraic code-excited linear prediction (ACELP) technique is recommended in AMR-WB, and it is noted that most of the complexity in the ACELP structure comes from the codebook search. In this paper, a new method is proposed for codebook search based on the behavior of backward filtered target signal, d(n), introduced in ITU-T G.722.2 recommendation. To optimize the proposed scheme, five optimization algorithms (i.e., modified genetic algorithm, particle swarm optimization with dynamic inertia weight, bee colony optimization, modified differential evolution, and imperialist competition algorithm) are investigated. Experimental results show that the reduction in codebook search operations of the proposed method is able to reach up to 59 percent as compared with ITU-T G.722.2 recommendation. Meanwhile, BCO-based codebook search scheme has better convergence speed without significant degradation in quality metrics, such as segmental signal-to-noise ratio, mean opinion score, and perceptual evaluation of speech quality, when used in an AMR-WB speech codec.

Context-Based Adaptive Arithmetic Encoding of EAVQ Indices

This paper presents a lossless compression algorithm for the binary indices of the embedded algebraic vector quantizer (EAVQ) used by the AMR-WB (Extended Adaptive Multi-Rate Wide Band) codec. We present a statical study of the EAVQ indices for diverse audio types (speech, music, etc.) and we discuss the design of the lossless algorithm including the choice of different strategies. The proposed algorithm combines run length encoding (RLE) and context-based arithmetic encoding to reduce the bitrate of the EAVQ indices by about 10% at the expense of 1% rise in complexity of the codec. The proposed algorithm can increase the segmental signal to noise ratio of about 9% at low rates for speech signals and improve the subjective scores in noisy channels by about 0.5 on a five-point scale if combined with an additional protection layer.

A new scheme for covert communication via 3G encoded speech

Mobile communication through 3G network has grown rapidly in recent years. It might be of interest to transmit secret messages over 3G voice channels. In this paper, we introduce a new covert communication scheme via Adaptive Multi-Rate Wideband (AMR-WB) encoded speech. An adaptive suboptimal pulse combination constrained (ASOPCC) method is presented to embed data on compressed speech signal of AMR-WB codec. The method takes advantage of the “redundancy”, created by non-exhaustive search of algebraic codebook, to encode secret information. An embedding factor η is used to control embedding bits. By properly setting η, ASOPCC can offer a better trade-off between speech quality and embedding capacity in the process of coding mode switching. Experimental results show that the proposed method is quite promising for both high capacity and good imperceptivity. Although ASOPCC is only applied to AMR-WB codec in this article, it can be further used by any other speech coding based on Algebraic Coded Exited Linear Prediction (ACELP).

Real-Time Implementation AMR-WB Algorithm in TMS320VC5509A DSP

Adaptive multi-rate wideband (AMR-WB) speech codec is the first standard for both wired and wireless universal broadband speech codec. Real-time implementation of AMR-WB algorithm in DSP has important practical significance and will accelerate its course of practice. The paper first designed the hardware platform and system software structure for real-time implementation of the AMR-WB algorithm, then introduced the transplantation of AMR-WB algorithm to the designed hardware system. The paper next discussed the real-time implementation of optimized algorithm on the hardware platform. Objective test results indicated the decoded speeches of real-time platform were bit exactly the same as test sequences. Synthetic speeches of real-time platform were very good in restoring the speaker’s voice characteristics by good intelligibility and naturalness.