Research on Pattern Recognition Technology for Music Teaching and Optimization of Its Teaching Framework

[1] Zhang, Y. (2017). Application of fuzzy neural network in music recognition. Revista de la Facultad de Ingenieria, 32(6), 171-180. Search in Google Scholar

[2] Liao, S. (2022). Construction and application of music teaching resources based on recurrent neural network. Mobile Information Systems, 2022(1), 8482265. Search in Google Scholar

[3] Zhou, M., & Gong, T. (2020). Optimization of multimedia computer-aided interaction system of vocal music teaching based on voice recognition. Computer-Aided Design and Applications, 8, 113-122. Search in Google Scholar

[4] Zhao, X. (2022). Evaluation of multimedia popular music teaching effect based on audio frame feature recognition technology. Advances in Multimedia, 2022(1), 1178100. Search in Google Scholar

[5] Pei, Z., & Wang, Y. (2021). Analysis of computer aided teaching management system for music appreciation course based on network resources. Computer-Aided Design and Applications, 19(S1), 1-11. Search in Google Scholar

[6] Liu, S. (2021, November). Music Tutor: Application of Chord Recognition in Music Teaching. In 2021 International Conference on Signal Processing and Machine Learning (CONF-SPML) (pp. 154-157). IEEE. Search in Google Scholar

[7] Chen, B. (2021). Research on the construction of college music teaching cloud platform based on data mining technology. Converter, 2021(8), 01-08. Search in Google Scholar

[8] Hou, Y. (2021, November). Handwritten note recognition based on digital music classroom teaching. In International Conference on Forthcoming Networks and Sustainability in the IoT Era (pp. 300-306). Cham: Springer International Publishing. Search in Google Scholar

[9] Jamshidi, F., Marghitu, D., & Chapman, R. (2021, July). Developing an online music teaching and practicing platform via machine learning: a review paper. In International conference on human-computer interaction (pp. 95-108). Cham: Springer International Publishing. Search in Google Scholar

[10] Wang, X. (2022). Design of vocal music teaching system platform for music majors based on artificial intelligence. Wireless Communications and Mobile Computing, 2022(1), 5503834. Search in Google Scholar

[11] Ye, Y., & Zhang, S. (2023). Development of music teaching system by using speech recognition and intelligent mobile remote device. International Journal of System Assurance Engineering and Management, 1-9. Search in Google Scholar

[12] Liu, N. (2022). Study on the Application of Improved Audio Recognition Technology Based on Deep Learning in Vocal Music Teaching. Mathematical Problems in Engineering, 2022(1), 1002105. Search in Google Scholar

[13] Liu, S. (2021, January). Multimedia interactive system of vocal music teaching based on voice recognition. In 2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) (pp. 599-602). IEEE. Search in Google Scholar

[14] Jiang, Q., & Jan, N. (2022). Application of Artificial Intelligence Technology in Music Education Supported by Wireless Network. Mathematical Problems in Engineering, 2022, 1-11. Search in Google Scholar

[15] Wang, Y. (2021). Research on handwritten note recognition in digital music classroom based on deep learning. Journal of Internet Technology, 22(6), 1443-1455. Search in Google Scholar

[16] Chen, N. (2021, September). Vocal music teaching evaluation model based on pattern recognition and voiceprint feature analysis. In 2021 4th International Conference on Information Systems and Computer Aided Education (pp. 2800-2804). Search in Google Scholar

[17] Wu, S. (2016, May). Research on the development of pattern recognition and applications on digital music recognition and creation. In 2016 2nd International Conference on Social Science and Technology Education (ICSSTE 2016) (pp. 646-651). Atlantis Press. Search in Google Scholar

[18] Alice Dorothy Stuart,Maja Ilić,Benno I Simmons & William J Sutherland. (2024). Sea stack plots: Replacing bar charts with histograms. Ecology and evolution(4),e11237-e11237. Search in Google Scholar

[19] Gómez Jaime,Guerra André,Ramos João P. G. & Tilli Paolo. (2024). Stability of the Faber-Krahn inequality for the short-time Fourier transform. Inventiones mathematicae(2),779-836. Search in Google Scholar

[20] Suvin Choi,Jong Ik Park,Cheol Ho Hong,Sang Gue Park & Sang Cheol Park. (2024). Accelerated construction of stress relief music datasets using CNN and the Mel-scaled spectrogram. PloS one(5),e0300607-e0300607. Search in Google Scholar

[21] Environmental And Public Health Journal Of. (2023). Retracted: Intelligent Classification Model of Music Emotional Environment Using Convolutional Neural Networks. Journal of environmental and public health9783043-9783043. Search in Google Scholar