基于深度学习的电子音乐信号辨识方法  

Electronic Music Signal Identification Method Based on Deep Learning

作　　者：甘泉 GAN Quan(Music Dream(Beijing)Technology Co.,Ltd.,Beijing 100029,China)

机构地区：[1]音乐梦想(北京)科技有限公司,北京100029

出　　处：《信息与电脑》2023年第5期54-56,61,共4页Information & Computer

摘　　要：由于传统音乐信号辨识方法存在精度低、效率差等缺陷,无法适应现代电子音乐发展速度,因此提出基于深度学习的电子音乐信号辨识方法。首先,采集电子音乐信号,通过预加重、加窗分帧操作预处理信号,剔除夹杂的干扰信号;其次,建立一个深度学习模型,利用模型训练、测试实现电子音乐信号辨识;最后,进行实验对比分析。实验结果表明,本文设计方法对多类型的电子音乐信号辨识正确率为96.42%,辨识时间为1.82s,优于其他方法。Because of the shortcomings of traditional music signal identification methods such as low accuracy and low efficiency,which cannot adapt to the development speed of modem electronic music,a method of electronic music signal identification based on deep learning is proposed.Firstly,the electronic music signal is collected,and the signal is preprocessed by pre-emphasis,windowing and frame division to eliminate the mixed interference signal.Secondly,a deep learning model is established,and the electronic music signal identification is realized by model training and testing.Finally,the experiment is compared and analyzed.The experimental results show that the design method in this paper has a recognition accuracy of 96.42%and a recognition time of 1.82 seconds for multiple types of electronic music signals,which is superior to other methods.

关 键 词：深度学习 电子音乐 信号辨识 辨识方法 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]