Dynamic forward error correction algorithm over IP network services for ITU-T G.722.2 codec

In this paper, we propose an improved packet loss concealment (PLC) algorithm for ACELP-based speech coders in order to improve the quality of decoded speech at the receiver. Conventional receiver-based PLC algorithms in the AMR-WB+ speech codec are usually based on speech correlations to reconstruct the decoded speech of the lost frames by using parameter information obtained from the previous or adjacent correctly received frames. However, this approach has difficulties in reconstructing accurate voice signals when consecutive packet loss and bursts of packet loss occur. Thus, we propose a new PLC approach based on data-driven principle to recover the Immittance Spectral Frequen- cy (ISF) coefficients of lost packet, referring to pitch period parameters of adjacent correctly received voice packets. The proposed PLC algorithm is designed for ACELP-based audio codec. We make the performance comparison between the data-driven method and the PLC algorithm currently employed in AMR-WB+ speech codec through the PESQ objective evaluation test and MOS subjective evaluation test. The results prove that our algorithm can achieve better speech recov- ery quality than original PLC algorithm employed in AMR-WB+ speech codec.

This letter proposes a degradation and cognition model to estimate speech quality impairment because of packet loss concealment (PLC) algorithm implemented in the speech CODEC SILK. By considering the fact that the quality degradation caused by packet loss is highly related to the PLC algorithm, the impact of quality degradation on various types of previous and lost packet classes is analyzed. Then, the PLC effects to the proposed class types are measured by the class conditional expectation of the degradation scores. Finally, the cognition module is derived to estimate the total quality degradation in a mean opinion score (MOS) scale. When assessed for correlation with subject test results, the correlation coefficient of the encoder-based class model is 0.93, and that of the decoder-based model is 0.87.

In this paper, a Packet Loss Concealment (PLC) algorithm for ITU-G.722.2 speech coder is proposed in order to improve the decoded speech quality under burst packet loss conditions over packet-switched networks. First, we evaluated the repetition of the last received frame method in order to improve the concealment of lost frames. Then, we made a statistical study to evaluate the correlation between parameters values of adjacent frames. Finally, we present a new PLC method for ITU-G.722.2 by proposing an efficient approach to sending the side information to improve concealment of the lost frames and to resynchronize the encoder and decoder. The proposed method significantly improves the robustness of the ITU-G.722.2 codec against packet losses for voice over networks services. Tests in terms of Wideband Perceptual Evaluation of Speech Quality Mean Opinion Score (WB-PESQ MOS) quality measure and MUlti-Stimulus test with Hidden Reference and Anchor (MUSHRA) evaluation confirm the superiority of our proposed method against the PLC method embedded in G.722.2.

This article presents ITU-T G.722 appendix IV which is a packet loss concealment (PLC) algorithm recently standardized by ITU-T for G.722 decoding in the presence of frame erasures. This algorithm is suitable for applications that may encounter frame erasures or packet losses with a special focus on complexity constraints For example, G.722 appendix IV is very suitable for DECT next generation and VoIP using low cost devices. Besides, we also describe some minor algorithmic modifications to G.722 appendix IV that improve subjective quality. We discuss G.722- PLC performance based on formal ITU-T test results as well as additional informal experiments.

This paper presents a comparison of end-to-end recovery and control methods for the ITU-T G.729 CS-ACELP codec operating at 8 Kbps. We have tested Media independent forward error correction (FEC) parity 3, Media independent FEC parity 4 and Media specific FEC combined with queue management methods namely Drop Tail, Predictive Loss Pattern (PLoP) and Random Early Detection (RED). The performance measures using perceptual evaluation of speech quality (PESQ) tests under various packet loss conditions prove that Media independent FEC parity 3 combined with RED algorithm give better results.

In this work, we present a dynamic channel coding scheme for robust transmission of JPEG2000 codestreams over Mobile Ad-hoc Networks (MANET). The proposed system, based on dynamic Forward Error Correction (FEC) rate allocation allied to layered Unequal Error Protection (UEP), is implemented according to the main recommendations of Wireless JPEG2000 standard final draft. We demonstrate that dynamic FEC rate allocation outperforms a priori FEC rate allocation. Going straightforward we validate the proposed scheme by deriving interesting results from Motion JPEG2000 video streaming over real MANET data traces.This application, developed within the European IST WCAM project, validates wireless JPEG2000 standards recommendations and is a step toward guaranteeing Quality of Service (QoS) in wireless JPEG2000 based data streaming systems.

A class of packet loss concealment algorithms for speech coding is presented. It generates the replacement waveform for the lost frame by direct extrapolation of the past speech waveform, with or without look-ahead. The ITU-T G.722 Appendix III standard is based on it. When a future frame is unavailable (without look-ahead), the PLC algorithm gives significantly better speech quality than G.711 Appendix I - by about 0.2 PESQ for high packet loss rates. When a future frame is available (with look-ahead), the PLC algorithm uses the decoded speech waveform in the future frame to guide the pitch contour of waveform extrapolation during the lost frame such that the extrapolated waveform is phase-aligned with the decoded waveform after the packet loss. This technique further improved PESQ by another 0.2 for high packet loss rates.

Packet loss concealment (PLC) at a receiver has a substantial effect on the speech quality in Voice over IP. Most conventional PLC systems have largely relied upon variations of signal repetition and overlap-add interpolation which can produce speech signals that do not follow the larger overall statistical trends. In this paper, we demonstrate how Hidden Markov Models can be utilized to effect PLC based on statistical signal processing. In particular, we show how HMM-based PLC yields conditional density functions that can be utilized by various statistical estimation methods that produce signal parameter estimates that produce more natural variation than conventional PLC methods, thereby providing much better speech quality.

In this paper, we compare air‐conducted (AC) speech with bone‐conducted (BC) speech for the purpose of utilizing them in packet loss concealment (PLC) for speech quality of voice over internet protocol (VoIP). Instead of the autocorrelation method of linear prediction (LP), which was utilized in the conventional PLC techniques, we employ the modified covariance (MC) method. The MC method provides accurate LP estimation from short input data samples and avoids the numerical problem the autocorrelation method suffers from. The lost frame is compensated from both forward and backward directions in which linear gain and weighting are applied. When BC speech is used as the input speech data for PLC in the case where the speech sender is in noisy environments, BC speech behaves more accurately than the corresponding AC speech, resulting in an excellent performance of the LP‐based PLC technique. This unveils a useful use of BC speech in speech information systems. Experiments show that in severe noise environments of AC speech‐to‐noise ratio being less than 10 dB, BC speech is superior to AC speech for PLC. It is also shown that the transmitted BC speech is more accurately reconstructed for PLC than transmitted AC speech is done. © 2023 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Pervasive computing with voice application service must be providing unprecedented levels of technology in order to adapt the continually changed computing resources in ubiquitous environment. A number of conditions differ from the speech signal over IP network with heterogeneous devices while voice traffic is transported by packet-based in ubiquitous environment. In this paper, voice signals in packet loss and noise is controlled for the guaranteed quality of service (QoS) on the IP network which are responsible for digitizing, encoding, decoding, and playing out the speech signal. We implement the algorithms of packet loss concealment (PLC) and noise reduction, which is called PEA (pervasive environment adaptation)-PLC, PEA-noise reduction together, for providing high quality voice-based pervasive computing services. The proposed PEA-PLC algorithms are applied as post-processing after decoding on devices, and then PEA-noise reduction method is applied as pre-processing before speech coding. The proposed PEA-algorithms for packet loss and noise are applied in G.729A codec optimally using mobile-softphone and a 1-port gateway PSTN phone system. The performances of the proposed methods are evaluated by the PESQ measurement in various packet loss and noisy conditions

Since the G.722 wideband speech codec offers higher quality and naturalness than G.711, is low in complexity, has low delay, and tandems well with other codecs, it is an attractive codec for voice over IP and voice over wireless LANs. However, packet losses in G.722 not only require good concealment of the lost frame, but a lost frame results in a mismatch of the encoder/decoder states for the next correctly received frame following the lost frame. Although proprietary schemes exist, the G.722 codec has no standardized packet loss concealment (PLC) method. We present a new PLC method for G.722 and propose an efficient approach to sending the side information to resynchronize the encoder and decoder that greatly improves the robustness of the G.722 codec to packet losses

High-quality and high-performance real-time interactive video streaming requires both keeping the highest data transmission rate and minimizing data packet loss to achieve the best possible streaming quality. TCP-friendly rate control (TFRC) is the most widely recognized mechanism for achieving relatively smooth data transmission while competing fairly with TCP flows. However, because its data transmission rate depends largely on packet loss conditions, high-quality real-time streaming suffers from a significant degradation of streaming quality due to both a reduction in the data transmission rate and data packet losses. This paper proposes the dynamic probing forward error correction (DP-FEC) mechanism that is effective for high-quality real-time streaming to maximize the streaming quality in a situation in which competing TCP flows pose packet losses to the streaming flow. DP-FEC estimates the network condition by dynamically adjusting the degree of FEC redundancy while trying to recover lost data packets. It effectively utilizes network resources and adjusts the degree of FEC redundancy to improve the playback quality at the user side while minimizing the performance impact of competing TCP flows. We describe the DP-FEC algorithm and evaluate its effectiveness using an NS-2 simulator. The results show that by effectively utilizing network resources, DP-FEC enables to retain higher streaming quality while minimizing the adverse condition on TCP performance, thus achieving TCP friendliness.

The growth in the power and connectivity of the Internet has sparked an even larger growth in streaming media. The sheer number of possible users and applications at any point in time raises the probability of streaming multimedia flows encountering congestion. To overcome short-term congestion and avoid long-term congestion collapse, there is a growing consensus that Internet applications must be TCP-Friendly, with proposed approaches to detect and punish non-TCP friendly flows. Unlike TCP, new TCP-friendly streaming media protocols refrain from retransmissions to avoid delay and jitter, but they are susceptible to quality degradation from packet loss. While multimedia applications can tolerate some data loss, excessive packet loss during congestion yields unacceptable media quality. Since video encoding involves interframe dependencies to achieve high compression rates, the random dropping of packets by routers can seriously degrade video quality. For example, as little as 3% MPEG packet loss can cause 30% of the frames to be undecodable. Streaming media flows often utilize lower latency repair approaches, such as Forward Error Correction (FEC), in conjunction with TCP-Friendly protocols to deliver streaming applications over the Internet. However, FEC requires redundant repair data to be added to the original video stream. Current approaches use either apriori, static FEC choices or adapt FEC to perceived packet loss on the network without regard to TCP-Friendly data rate constraints. When a streaming video operates within TCP-Friendly bitrate limits, adding FEC will reduce the effective transmission rate of the original video content.

Packet loss may affect a wide range of applications that use voice over IP (VoIP), e.g. video conferencing. In this paper, we investigate a time-domain convolutional recurrent network (CRN) for online packet loss concealment. The CRN comprises a convolutional encoder-decoder structure and long short-term memory (LSTM) layers, which have been shown to be suitable for real-time speech enhancement applications. Moreover, we propose lookahead and masked training to further improve the performance of the CRN framework. Experimental results show that the proposed system outperforms a baseline system using only LSTM layers in terms of two objective metrics – perceptual evaluation of speech quality (PESQ) and short-term objective intelligibility (STOI); it also reduces the word error rate (WER) more than the baseline when used as a frontend for speech recognition. The advantage of the proposed system is also verified in a subjective evaluation by the mean opinion score (MOS).

Phase unwrapping based packet loss concealment using deep neural networks