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Remote Music Learning Based on Wireless Sensors Supporting 6G and CPS

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Abstract

This paper presents the Hybrid Dilated Convolutional Neural Network (HDCNN) based remote music learning process, a novel method that uses Wireless Sensors, 6G technology, and Cyber-Physical Systems (CPS). The HDCNN design effectively improves the model's capacity to evaluate high-resolution audio inputs by combining several advanced neural network techniques with dilated convolutions. By adding dilated convolutions, the HDCNN can capture a broader range of musical details and patterns important for effective music teaching and maintaining computational efficiency. Due to the real-time processing requirements of remote music learning, where latency and data throughput are major problems, this capability is significant. This architecture provides a flexible, effective solution for the challenging task of remote music learning in addition to addressing the shortcomings of conventional CNN, in processing complex audio input. A dynamic and adaptable learning platform is supported by the HDCNN's ability to understand difficult musical patterns through variable dilation rates and a multi-scale processing method. Our methodology, which bridges the gap between digital and physical learning locations using cutting-edge technology, marks an important advance in remote music learning. The upcoming sections clearly illustrate the proposed architecture efficiency in remote music learning.

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Availability of Data and Material

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Turchet, L., Fischione, C., Essl, G., Keller, D., & Barthet, M. (2018). Internet of musical things: Vision and challenges. Ieee access, 6, 61994–62017.

    Article  Google Scholar 

  2. Ma, X., Dong, Z., Quan, W., Dong, Y., & Tan, Y. (2023). Real-time assessment of asphalt pavement moduli and traffic loads using monitoring data from built-in sensors: Optimal sensor placement and identification algorithm. Mechanical Systems and Signal Processing, 187, 109930.

    Article  Google Scholar 

  3. Yin, F., Fritsche, C., Jin, D., Gustafsson, F., & Zoubir, A. (2015). M, Cooperative localization in WSNs using gaussian mixture modeling: Distributed ECM algorithms. IEEE Transactions on Signal Processing, 63(6), 1448–1463.

    Article  Google Scholar 

  4. Li, S., Chen, J., Peng, W., Shi, X., & Bu, W. (2023). A vehicle detection method based on disparity segmentation. Multimedia Tools and Applications, 82(13), 19643–19655.

    Article  Google Scholar 

  5. Chen, J., Song, Y., Li, D., Lin, X., Zhou, S., & Xu, W. (2024). Specular removal of industrial metal objects without changing lighting configuration. IEEE Transactions on Industrial Informatics, 20(3), 3144–3153.

    Article  Google Scholar 

  6. Xu, H., Li, Q., & Chen, J. (2022). Highlight removal from a single grayscale image using attentive GAN. Applied Artificial Intelligence, 36(1), 1988441.

    Article  Google Scholar 

  7. Seng, W. (2022). Remote music teaching classroom based on machine learning and 5G network station. Wireless Communications and Mobile Computing

  8. Li, J., Han, L., Zhang, C., Li, Q., & Liu, Z. (2023). Spherical convolution empowered viewport prediction in 360 video multicast with limited FoV feedback. ACM Transactions on Multimedia Computing, Communications and Applications, 19(1), 1–23.

    Article  Google Scholar 

  9. Chen, L., Song, L., Chakareski, J., & Xu, J. (2019). Collaborative content placement among wireless edge caching stations with time-to-live cache. IEEE transactions on multimedia, 22(2), 432–444.

    Article  Google Scholar 

  10. Li, J., Zhang, C., Liu, Z., Hong, R., & Hu, H. (2023). Optimal volumetric video streaming with hybrid saliency based tiling. IEEE Transactions on Multimedia, 25, 2939–2953.

    Article  Google Scholar 

  11. Solanki, A., & Pandey, S. (2022). Music instrument recognition using deep convolutional neural networks. International Journal of Information Technology, 14(3), 1659–1668.

    Article  Google Scholar 

  12. Sarkar, R., Choudhury, S., Dutta, S., Roy, A., & Saha, S. K. (2020). Recognition of emotion in music based on deep convolutional neural network. Multimedia Tools and Applications, 79, 765–783.

    Article  Google Scholar 

  13. Dai, M., Sun, G., Yu, H., & Niyato, D. (2024). Maximize the long-term average revenue of network slice provider via admission control among heterogeneous slices. IEEE/ACM Transactions on Networking, 32(1), 745–760.

    Article  Google Scholar 

  14. Lei, X., Pan, H., & Huang, X. (2019). A dilated CNN model for image classification. IEEE Access, 7, 124087–124095.

    Article  Google Scholar 

  15. Dai, M., Luo, L., Ren, J., Yu, H., & Sun, G. (2022). PSACCF: Prioritized online slice admission control considering fairness in 5G/B5G Networks. IEEE Transactions on Network Science and Engineering, 9(6), 4101–4114.

    Article  Google Scholar 

  16. Sun, G., Xu, Z., & Yu, H. (2021). Chang, V, dynamic network function provisioning to enable network in box for industrial applications. IEEE Transactions on Industrial Informatics, 17(10), 7155–7164.

    Article  Google Scholar 

  17. Liu, H., Jiang, K., Gamboa, H., Xue, T., & Schultz, T. (2022). Bell shape embodying zhongyong: The pitch histogram of traditional chinese anhemitonic pentatonic folk songs. Applied Sciences, 12(16), 8343.

    Article  Google Scholar 

  18. Pandeya, Y. R., & Lee, J. (2021). Deep learning-based late fusion of multimodal information for emotion classification of music video. Multimedia Tools and Applications, 80, 2887–2905.

    Article  Google Scholar 

  19. Wilson, R. (2023). Aesthetic and technical strategies for networked music performance. AI & society, 38(5), 1871–1884.

    Article  Google Scholar 

  20. Li, J., Li, J., Wang, C., Verbeek, F. J., Schultz, T., & Liu, H. (2024). MS2OD: Outlier detection using minimum spanning tree and medoid selection. Machine Learning: Science and Technology, 5(1), 15025.

    Google Scholar 

  21. Khan, D., Alonazi, M., Abdelhaq, M., Al Mudawi, N., Algarni, A., Jalal, A., & Liu, H. (2024). Robust human locomotion and localization activity recognition over multisensory. Frontiers in Physiology, 15, 1344887.

    Article  Google Scholar 

  22. Cao, K., Wang, B., Ding, H., Lv, L., Tian, J., Hu, H., & Gong, F. (2021). Achieving reliable and secure communications in wireless-powered NOMA systems. IEEE Transactions on Vehicular Technology, 70(2), 1978–1983.

    Article  Google Scholar 

  23. Sudarma, M., & Harsemadi, I. G. (2017). Design and analysis system of KNN and ID3 algorithm for music classification based on mood feature extraction. International Journal of Electrical and Computer Engineering, 7(1), 486.

    Google Scholar 

  24. Huang, C., Han, Z., Li, M., Wang, X., & Zhao, W. (2021). Sentiment evolution with interaction levels in blended learning environments: Using learning analytics and epistemic network analysis. Australasian Journal of Educational Technology, 37(2), 81–95.

    Article  Google Scholar 

  25. Huang, C., Tu, Y., Han, Z., Jiang, F., Wu, F., & Jiang, Y. (2023). Examining the relationship between peer feedback classified by deep learning and online learning burnout. Computers & Education, 207, 104910.

    Article  Google Scholar 

  26. Li, B., Li, G., & Luo, J. (2021). Latent but not absent: The ‘long tail’ nature of rural special education and its dynamic correction mechanism. PLoS ONE, 16(3), 0242023.

    Google Scholar 

  27. Chen, G., Chen, P., Wang, Y., Zhu, N. (2023) Research on the development of an effective mechanism of using public online education resource platform: TOE model combined with FS-QCA. Interactive Learning Environments

  28. Cheng, D., Chen, L., Lv, C., Guo, L., & Kou, Q. (2022). Light-Guided and Cross-Fusion U-Net for Anti-Illumination Image Super-Resolution. IEEE Transactions on Circuits and Systems for Video Technology, 32(12), 8436–8449.

    Article  Google Scholar 

  29. Sheng, H., Wang, S., Yang, D., Cong, R., Cui, Z., & Chen, R. (2023). Cross-view recurrence-based self-supervised super-resolution of light field. IEEE Transactions on Circuits and Systems for Video Technology, 33(12), 7252–7266.

    Article  Google Scholar 

  30. Cong, R., Sheng, H., Yang, D., Cui, Z., & Chen, R. (2024). Exploiting spatial and angular correlations with deep efficient transformers for light field image super-resolution. IEEE Transactions on Multimedia, 26, 1421–1435.

    Article  Google Scholar 

  31. Pan, S., Xu, G. J. W., Guo, K., Park, S. H., Ding, H. (2023) Video-based engagement estimation of game streamers: An interpretable multimodal neural network approach. IEEE Transactions on Games

  32. Fu, C., Yuan, H., Xu, H., Zhang, H., & Shen, L. (2023). TMSO-Net: Texture adaptive multi-scale observation for light field image depth estimation. Journal of Visual Communication and Image Representation, 90, 103731.

    Article  Google Scholar 

  33. Tian, G., Hui, Y., Lu, W., & Tingting, W. (2023). Rate-distortion optimized quantization for geometry-based point cloud compression. Journal of Electronic Imaging, 32(1), 13047.

    Google Scholar 

  34. Xing, J., Yuan, H., Hamzaoui, R., Liu, H., & Hou, J. (2023). GQE-Net: A graph-based quality enhancement network for point cloud color attribute. IEEE Transactions on Image Processing, 32, 6303–6317.

    Article  Google Scholar 

  35. Hou, X., Xin, L., Fu, Y., Na, Z., Gao, G., Liu, Y., & Chen, T. (2023). A self-powered biomimetic mouse whisker sensor (BMWS) aiming at terrestrial and space objects perception. Nano Energy, 118, 109034.

    Article  Google Scholar 

  36. Bo, C., Jiangping, H., & Bijoy, G. (2023). Finite-time observer based tracking control of heterogeneous multi-AUV systems with partial measurements and intermittent communication. SCIENCE CHINA Information Sciences. https://doi.org/10.1007/s11432-023-3903-6

    Article  Google Scholar 

  37. Hu, J., Wu, Y., Li, T., & Ghosh, B. K. (2019). Consensus control of general linear multiagent systems with antagonistic interactions and communication noises. IEEE Transactions on Automatic Control, 64(5), 2122–2127.

    Article  MathSciNet  Google Scholar 

  38. Chen, B., Hu, J., Zhao, Y., & Ghosh, B. K. (2022). Finite-time velocity-free rendezvous control of multiple AUV systems with intermittent communication. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(10), 6618–6629.

    Article  Google Scholar 

  39. Zhao, L., Xu, H., Qu, S., Wei, Z., Liu, Y. (2024). Joint trajectory and communication design for UAV-assisted symbiotic radio networks. IEEE Transactions on Vehicular Technology

  40. Tang, Q., Qu, S., Zhang, C., Tu, Z., & Cao, Y. (2024). Effects of impulse on prescribed-time synchronization of switching complex networks. Neural Networks, 174, 106248.

    Article  Google Scholar 

  41. Xuemin, Z., Ying, R., Zenggang, X., Haitao, D., Fang, X., & Yuan, L. (2023). Resource-constrained and socially selfish-based incentive algorithm for socially aware networks. Journal of Signal Processing Systems, 95(12), 1439–1453.

    Article  Google Scholar 

  42. Xu, H., Han, S., Li, X., & Han, Z. (2023). Anomaly traffic detection based on communication-efficient federated learning in space-air-ground integration network. IEEE Transactions on Wireless Communications, 22(12), 9346–9360.

    Article  Google Scholar 

  43. Zhou, G., Xu, C., Zhang, H., Zhou, X., Zhao, D., Wu, G., & Zhang, L. (2022). PMT gain self-adjustment system for high-accuracy echo signal detection. International Journal of Remote Sensing, 43(19–24), 7213–7235.

    Article  Google Scholar 

  44. Zhou, G., Zhao, D., Zhou, X., Xu, C., Liu, Z., Wu, G., & Zou, L. (2022). An RF amplifier circuit for enhancement of echo signal detection in bathymetric LiDAR. IEEE Sensors Journal, 22(21), 20612–20625.

    Article  Google Scholar 

  45. Wu, Z., Zhu, H., He, L., Zhao, Q., Shi, J., & Wu, W. (2023). Real-time stereo matching with high accuracy via spatial attention-guided upsampling. Applied Intelligence, 53(20), 24253–24274.

    Article  Google Scholar 

  46. Liu, Z., Kong, X., Liu, S., & Yang, Z. (2023). Effects of computer-based mind mapping on students’ reflection, cognitive presence, and learning outcomes in an online course. Distance Education, 44(3), 544–562.

    Article  Google Scholar 

  47. Jiao, B., Qiao, J., Jia, S., Liu, R., Wei, X., Yun, S., Cong, B. (2024). Low stress TSV arrays for high-density interconnection. Engineering

  48. Tian, W., Zhao, Y., Hou, R., Dong, M., Ota, K., Zeng, D., & Zhang, J. A. (2023). Centralized control-based clustering scheme for energy efficiency in underwater acoustic sensor networks. IEEE Transactions on Green Communications and Networking, 7(2), 668–679.

    Article  Google Scholar 

  49. Jiang, Z., Xu, C. (2023). Disrupting the technology innovation efficiency of manufacturing enterprises through digital technology promotion: an evidence of 5g technology construction in China. IEEE Transactions on Engineering Management

  50. Cheng, B., Wang, M., Zhao, S., Zhai, Z., Zhu, D., & Chen, J. (2017). Situation-aware dynamic service coordination in an IoT environment. IEEE/ACM Transactions on Networking, 25(4), 2082–2095.

    Article  Google Scholar 

  51. Ban, Y., Liu, Y., Yin, Z., Liu, X., Liu, M., Yin, L., & Zheng, W. (2024). Micro-directional propagation method based on user clustering. Computing and Informatics, 42(6), 1445–1470.

    Article  Google Scholar 

  52. Dang, W., Cai, L., Liu, M., Li, X., Yin, Z., Liu, X., & Zheng, W. (2024). Increasing text filtering accuracy with improved LSTM. Computing and Informatics, 42(6), 1491–1517.

    Article  Google Scholar 

  53. Cao, B., Zhao, J., Yang, P., Gu, Y., Muhammad, K., Rodrigues, J. J. P. C., & de Albuquerque, V. H. C. (2020). Multiobjective 3-D topology optimization of next-generation wireless data center network. IEEE Transactions on Industrial Informatics, 16(5), 3597–3605.

    Article  Google Scholar 

  54. Cao, B., Zhao, J., Gu, Y., Fan, S., & Yang, P. (2020). Security-aware industrial wireless sensor network deployment optimization. IEEE Transactions on Industrial Informatics, 16(8), 5309–5316.

    Article  Google Scholar 

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  1. School of Arts, Hunan University of Information Technology, Changsha, Hunan, China

    Xuelinzi Bai

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Xuelinzi Bai: Conceptualization, Methodology, Formal analysis, Validation, Resources, Supervision, Writing—original draft, Writing—review & editing.

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Correspondence to Xuelinzi Bai.

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Bai, X. Remote Music Learning Based on Wireless Sensors Supporting 6G and CPS. Wireless Pers Commun (2024). https://doi.org/10.1007/s11277-024-11147-7

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