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The statistical measurements and neural network analysis of the effect of musical education to musical hearing and sensing

机译:音乐教育对听觉和听觉影响的统计量测和神经网络分析

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Department of Musical Education, Faculty of Education, Cazi University, 06200 Teknikokullar, Ankara, Turkey;Department of Musical Education, Faculty of Education, Cazi University, 06200 Teknikokullar, Ankara, Turkey;%This work presents the help of music education to musical hearing, the sensing of hearing at the end of education, and the affection of hearing levels of young people. In this study, neural network is used for classification of students using musical hearing and sensing. We demonstrate that machine learning can be used to predict the students musical perception, who entered to the Education Faculty, using neural networks. The pure tone audiometric measurements were realized for the evaluation of hearing at the frequencies 250, 500, 1000, 2000, and 8000 Hz. The evaluation of musical hearing for the students was achieved as: single tone-vertical hearing, poly tone-horizontal hearing and melody and rhythm hearing. The testing of musical hearing and sensing of students were compared with the test after two-year education. It was observed that the tests after two-year education offered good performances at all frequency level and this is meaningful in statistically, While musical hearing sensitivity is significantly high in horizontal and rhythm hearing tests, it is not changed in vertical hearing tests. Our results show that by using musical hearing and sensing our neural network classifies students whether they are at musical Education Department or other educational department of Education Faculty at a success rate of 92% and 88%, respectively.
机译:卡齐大学教育学院音乐教育系,土耳其安卡拉06200 Teknikokullar;卡齐大学教育学院音乐教育系,土耳其安卡拉06200 Teknikokullar;%这项工作为听觉音乐提供了音乐教育的帮助,教育结束时的听觉感知以及年轻人的听力水平影响。在这项研究中,神经网络用于通过听觉和听觉对学生进行分类。我们证明了机器学习可用于预测使用神经网络进入教育学院的学生的音乐知觉。实现了纯音测听测量,以评估在250、500、1000、2000和8000 Hz频率下的听力。对学生的音乐听觉评价为:单音-垂直听,多音-水平听和旋律与节奏听。将学生的听觉和听觉测试与两年教育后的测试进行了比较。据观察,两年的教育后的测验在所有频率水平上均表现良好,这在统计学上是有意义的。尽管水平和节奏听觉测验中的音乐听力敏感性显着较高,但在垂直听觉测验中并未改变。我们的结果表明,通过使用听觉和感知,我们的神经网络可以将学生处于音乐教育系还是教育学院其他教育系进行分类,分别为92%和88%。

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