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RNN-based signal classification for hybrid audio data compression

COMPUTING 2020年第3期102卷 813-827页

作者： Tu, Weiping Yang, Yuhong Du, Bo Yang, Wanzhao Zhang, Xiong Zheng, Jiaxi Wuhan Univ Sch Comp Sci Natl Engn Res Ctr Multimedia Software Wuhan Hubei Peoples R China

Audio data are a fundamental component of multimedia big data. Switched audio codec has been proved to be efficient for compressing a large range of audio signals at low bit rates. However, coding quality strongly relies on an exact classification of the input signals. Two coding mode selection methods are adopted in AMR-WB+, the state-of-the-art switched audio coder. The closed-loop method obtains good quality, but it has a high computation complexity. Conversely, the open-loop method reduces complexity but has unsatisfactory coding quality. Therefore, in this study, a speech/music discrimination based on a recurrent neural network (RNN) model is investigated to improve the coding performance of AMR-WB+. An RNN model is chosen for its outstanding performance on processing time series. The recurrent structure of RNN makes it capable of learning and making full use of the temporal information of the input sequences to make up for the deficiencies of the short-term features. We quantitatively analyze the quality loss caused by two types of misclassification and the tune parameter of the classifier to improve the signal-to-noise ratio (SNR) of the synthesized signals. The experimental results show that the proposed method increases the accuracy of the mode selection with a rate of 18% and the coding quality of 0.21 dB in segmental SNR in comparison with the open-loop method. Moreover, it reduces the computational complexity by about 43% in comparison with the closed-loop method in AMR-WB+.

关键词： Data compression Speech music discrimination Recurrent neural networks coding mode selection

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An RNN-Based Speech-Music Discrimination Used for Hybrid Audio Coder 24th

An RNN-Based Speech-Music Discrimination Used for Hybrid Aud...

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24th International Conference on MultiMedia modeling (MMM)

作者： Yang, Wanzhao Tu, Weiping Zheng, Jiaxi Zhang, Xiong Yang, Yuhong Song, Yucheng Wuhan Univ Sch Comp Sci Natl Engn Res Ctr Multimedia Software Wuhan Hubei Peoples R China Wuhan Univ Shenzhen Res Inst Shenzhen Peoples R China

ISBN: (纸本)9783319736037;9783319736020

Hybrid coders are able to select coding mode for different types of audio data and obtain high coding efficiency in a universal scheme with low bitrate. The selection accuracy is critical to maintain the quality of decoded audio signal and the computational complexity of hybrid coder is also important due to various applications on mobile devices. In this paper, a low complexity coding mode selection method based on Recurrent Neural Networks (RNN) has been investigated to improve the coding performance of the state-of-the-art hybrid coder, AMR-WB+. A constraint is composed on the outputs of RNN by sigmoid function to improve SNR of the decoded audio signal. The experimental results show that the proposed method achieves almost similar quality of decoded audio signal with closed-loop method and comparable complexity with open-loop method in AMR-WB+ coder, outperforming some latest classification methods for this standard.

关键词： Hybrid audio coder Recurrent Neural Networks coding mode selection

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A Neural Network Based coding mode selection Scheme of Hybrid Audio Coder

A Neural Network Based Coding Mode Selection Scheme of Hybri...

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IEEE International Conference on Wireless Communications, Networking and Information Security (WCNIS)

作者： Wang, Mu-Liang Lee, Mn-Ta Shu Te Univ Dept Comp Sci & Informat Engn Kaohsiung Taiwan Kao Yuan Univ Dept Elect Engn Kaohsiung Taiwan

ISBN: (纸本)9781424458516

New generation mobile communication transfers multiple contents, thus, codec no longer processes specific audio signal content (speech or music) only, but has to process mixed audio signal content. As different audio signal types have different characteristics, they have to be processed by using proper coding core. Hybrid audio coder architecture can be adopted to improve the coding efficiency. The coder must determine signal type correctly in order to maintain the quality of decoded audio signal. The computational complexity of hybrid audio codec can be reduced if signal classification can be performed quickly. In this paper, a low complexity coding mode selection technique based on neural network has been investigated. The experimental results demonstrate that the proposed scheme enables a reduction of about 75 percent of the computational load of 3GPP AMR-WB+ coder. The degradation of SNR is about 0.4dB. The informal listening test shows that the quality degradation is almost negligible. The proposed scheme is more effective than the fast algorithm recommended in standard.

关键词： hybrid audio coder computational complexity coding mode selection neural network

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A Neural Network Based coding mode selection Scheme of Hybrid Audio Coder

A Neural Network Based Coding Mode Selection Scheme of Hybri...

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2010 IEEE International Conference Conferenhce on Wireless Communications,Networking and Information Security(2010 IEEE 无线通信、网络技术与信息安全国际会议 WCNIS)

作者： Mu-Liang Wang Mn-Ta Lee Department of Computer Science and Information Engineering Shu-Te University Kaohsiung County Taiwa Department of Electronic Engineering Kao Yuan University Kaohsiung County Taiwan R.O.C.

ISBN: (纸本)9781424458509

关键词： hybrid audio coder computational complexity coding mode selection neural network

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LOW COMPLEXITY INTRA mode selection FOR EFFICIENT DISTRIBUTED VIDEO coding

LOW COMPLEXITY INTRA MODE SELECTION FOR EFFICIENT DISTRIBUTE...

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IEEE International Conference on Multimedia and Expo

作者： Ascenso, Joao Pereira, Fernando Inst Super Engn Lisboa Lisbon Portugal Inst Super Tecn Lisbon Portugal Inst Telecomunicacoes Lisbon Portugal

ISBN: (纸本)9781424442904

Motion compensated frame interpolation (MCFI) is one of the most efficient solutions to generate side information (SI) in the context of distributed video coding. However, it creates SI with rather significant motion compensated errors for some frame regions while rather small for some other regions depending on the video content. In this paper, a low complexity Infra mode selection algorithm is proposed to select the most 'critical' blocks in the WZ frame and help the decoder with some reliable data for those blocks. For each block, the novel coding mode selection algorithm estimates the encoding rate for the Intra based and WZ coding modes and determines the best coding mode while maintaining a low encoder complexity. The proposed solution is evaluated in terms of rate-distortion performance with improvements up to 1.2 dB regarding a WZ coding mode only solution.

关键词： Distributed video coding Wyner-Ziv coding side information coding mode selection Intra coding

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Fast coding mode selection with rate-distortion optimization for MPEG-4 part-10 AVC/H.264

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2006年第12期16卷 1557-1561页

作者： Choi, Inchoon Lee, Jeyun Jeon, Byeungwoo Sungkyunkwan Univ Sch Informat & Commun Engn Kyonggi Do 440746 South Korea

The MPEG-4 Part-10 AVC/H.264 standard employs several powerful coding methods to obtain high compression efficiency. To reduce the temporal and spatial redundancy more effectively, motion compensation uses variable block sizes, and directional intra prediction investigates all available coding modes to decide the best one. When the rate-distortion (R-D) optimization technique is used, an encoder finds the coding mode having minimum R-D cost. Due to the large number of combinations of coding modes, the decision process requires extremely high computation. To reduce the complexity, we propose two methods: early SKIP mode decision and selective intra mode decision. In the simulation results, the proposed methods are verified to significantly reduce the entire encoding time by about 60% with only negligible coding loss.

关键词： coding mode selection early SKIP detection fast algorithm mode decision NIPEG-4 Part-10 AVC/H.264 selective intra coding

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Advances in recursive per-pixel end-to-end distortion estimation for robust video coding in H.264/AVC

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2007年第7期17卷 845-856页

作者： Yang, Hua Rose, Kenneth Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

This paper is focused on expanding the applicability of the recursive optimal per-pixel estimate (ROPE) of end-to-end distortion, to the H.264/AVC standard. One open question involves the complexity of cross-correlation terms that appear in the case of subpixel prediction and other pixel filtering operations. Several efficient model-based solutions are proposed. Another open question involves the largely ignored effects of rounding operations, whose cumulative impact may seriously degrade the estimate accuracy. Two approaches are proposed for rounding error compensation: one appeals to the maximum entropy principle, while a low complexity alternative is based on quantization theoretic approximations. The former effectively estimates the distribution of the decoder reconstruction, thereby significantly broadening the applicability of ROPE to all additive,distortion measures. Simulation results for H.264/AVC with 1/4-pel prediction show that the proposed ROPE extensions achieve fairly high estimation accuracy, while maintaining low complexity. Another set of results demonstrates the level of overall coding gains achievable by exploiting such improved end-to-end distortion estimation.

关键词： coding mode selection end-to-end distortion error resilience video coding

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Content-based FGS coding mode determination for video streaming over wireless networks

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2003年第10期21卷 1595-1603页

作者： Hung, BF Huang, CL Etron Technol Inc Hsinchu 300 Taiwan Natl Tsing Hua Univ Dept Elect Engn Hsinchu 300 Taiwan

Video streaming is the major subject of Amendment for MPEG-4 and it is developed in response to the growing needs on a video-coding standard for the video communication. The fine-granular scalability (FGS) combined with the temporal scalability addresses a variety of challenging problems in delivering video. The FGS video encoder makes the coding mode decision based on the video content and the current available bandwidth in order to achieve higher perceptual video quality. In this paper, we develop a mode selection method to find the most suitable scalable coding mode from six coding schemes: FGS, FGST, FGS-SE, and FGST with background composition based on the contents of the video sequences.

关键词： background composition coding mode selection fine-granular scalability (FGS) scalable video coding video streaming

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