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基于情感识别的音乐教学管理系统优化。

Optimization of the Music Teaching Management System Based on Emotion Recognition.

机构信息

Department of Public Arts, Henan College of Transportation, ZhengZhou 450000, China.

出版信息

Comput Intell Neurosci. 2022 May 9;2022:4568041. doi: 10.1155/2022/4568041. eCollection 2022.

DOI:10.1155/2022/4568041
PMID:35586091
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9110121/
Abstract

Along with the development of social informatization, computer has been widely used in daily teaching and the technical support teaching management system, which can greatly improve the quality of students and teachers' information sharing and teaching, and is an important part of college information construction. Teachers' personal information, teaching information query, teaching file management, students' attendance, students' results query, teachers' evaluation, and so on constitute the music teaching information management system. Based on the Internet of things technology and emotion recognition, this paper mainly describes the design idea of the music teaching management system software, function design, and implementation scheme. The realization process of each subfunction module and hardware and software of the system is described in detail. In view of the characteristics of music teaching management itself, combined with the actual situation of music teaching, to form the system structure analysis, database design and data exchange, and other aspects of exploration, in order to establish a practical music teaching management system.

摘要

随着社会信息化的发展，计算机已广泛应用于日常教学中，技术支持教学管理系统，可以大大提高师生信息共享和教学质量，是高校信息化建设的重要组成部分。教师个人信息、教学信息查询、教学文件管理、学生考勤、学生成绩查询、教师评价等构成了音乐教学信息管理系统。本文基于物联网技术和情感识别，主要描述了音乐教学管理系统软件的设计思想、功能设计和实现方案。详细描述了系统各子功能模块的实现过程以及系统的软硬件。针对音乐教学管理本身的特点，结合音乐教学的实际情况，形成系统结构分析、数据库设计和数据交换等方面的探索，建立实用的音乐教学管理系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/865f/9110121/9319cb76dfb2/CIN2022-4568041.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/865f/9110121/77091b01ad19/CIN2022-4568041.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/865f/9110121/0152a82ba8c9/CIN2022-4568041.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/865f/9110121/9319cb76dfb2/CIN2022-4568041.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/865f/9110121/77091b01ad19/CIN2022-4568041.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/865f/9110121/2b0a55741da7/CIN2022-4568041.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/865f/9110121/f9c0f53baa76/CIN2022-4568041.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/865f/9110121/da38e2c7a0a4/CIN2022-4568041.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/865f/9110121/0e9dff8ddbde/CIN2022-4568041.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/865f/9110121/62e93e99f578/CIN2022-4568041.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/865f/9110121/0152a82ba8c9/CIN2022-4568041.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/865f/9110121/9319cb76dfb2/CIN2022-4568041.008.jpg

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Compensated Fuzzy Neural Network-Based Music Teaching Ability Assessment Model.基于补偿模糊神经网络的音乐教学能力评估模型。
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Optimizing Performative Skills in Social Interaction: Insights From Embodied Cognition, Music Education, and Sport Psychology.优化社交互动中的表演技巧：来自具身认知、音乐教育和运动心理学的见解。
Front Psychol. 2019 Jul 16;10:1542. doi: 10.3389/fpsyg.2019.01542. eCollection 2019.