Open AccessAnalysis of the Current Situation of Piano Education in Colleges and Universities in the Information Age and Research on Countermeasures
Author(s) -
Yuan Shuhui
Publication year - 2021
Publication title -
converter
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.104
H-Index - 1
ISSN - 0010-8189
DOI - 10.17762/converter.232
Subject(s) - chord (peer to peer) , piano , computer science , improvisation , correctness , midi , gesture , initialization , speech recognition , robustness (evolution) , computer vision , artificial intelligence , multimedia , algorithm , acoustics , programming language , database , biochemistry , chemistry , physics , gene , operating system
In view of the low application ability of piano improvisational accompaniment of music majors, this paper proposes a method of big data combined with MIDI keyboard and Kinect depth sensor to achieve the purpose of recognizing chord progression and judging fingering when students perform, and realizes the auxiliary teaching system. Firstly, the information of color and depth images is obtained, and the state transition diagram of chord transposition and chord gesture template library are constructed as the system initialization conditions. Secondly, using the traditional skin color modeling and background difference method as well as the current depth data, the gesture recognition is realized by template matching. Finally, the correctness of chord progression is judged, and comprehensive fingering application is used to score and evaluate. The experimental results show that the system has high robustness and can be effectively applied to piano teaching.