AUTHOR=Li Huizi 

TITLE=Piano Education of Children Using Musical Instrument Recognition and Deep Learning Technologies Under the Educational Psychology

JOURNAL=Frontiers in Psychology

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2021.705116

DOI=10.3389/fpsyg.2021.705116

ISSN=1664-1078

ABSTRACT=The aim is to enhance quality education in the traditional pre-school piano education. DL (Deep Learning) technology is applied to children's piano education to improve their interest in music learning. Firstly, the problems of the traditional children's piano education are analyzed, the teaching patterns are discussed under educational psychology, and a targeted music education plan is established. Secondly, musical instrument recognition technology is introduced, and the musical instrument recognition model is implemented based on DL. Thirdly, the proposed model is applied to children's piano education to guide students’ music learning and improve their interest in piano learning, and the feature recognition and acquisition of the proposed model are improved. Finally, the different teaching patterns are comparatively analyzed through the QS (Questionnaire Survey). The experimental results show that the instrument recognition accuracy of HNN (Hybrid Neural Network) is 97.2%, and with the increase of iterations, the recognition error rate of the model decreases and stabilizes. Therefore, the proposed HNN based on DL for musical instrument recognition can accurately identify musical features. The QS results show that the introduction of musical instrument recognition technology in children's piano education can improve children's interest in piano learning. Therefore, the establishment of children's piano education patterns based on musical instrument recognition technology can improve the teaching effect of students' piano education. The research results provide a reference for the intellectualization of children's piano education.