神经网络音乐类型分类

IF 1.7 Q2 Engineering

Canadian Journal of Electrical and Computer Engineering-Revue Canadienne De Genie Electrique et Informatique Pub Date : 2020-01-01 DOI:10.1109/CJECE.2020.2970144

Nikki Pelchat, Craig M. Gelowitz

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引用次数: 10

摘要

近年来，神经网络在音乐类型分类方面取得了一定的成功。歌曲库、机器学习技术、输入格式和实现的神经网络类型的差异都取得了不同程度的成功。本文回顾了该领域中使用的一些机器学习技术。介绍了音乐类型分类的研究工作。该研究使用歌曲时间片生成的谱图图像作为神经网络的输入，将歌曲分类为各自的音乐类型。

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Neural Network Music Genre Classification

Music genre classification utilizing neural networks (NNs) has achieved some limited success in recent years. Differences in song libraries, machine learning techniques, input formats, and types of NNs implemented have all had varying levels of success. This article reviews some of the machine learning techniques utilized in this area. It also presents research work on music genre classification. The research uses images of spectrograms generated from timeslices of songs as the input into an NN to classify the songs into their respective musical genres.

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来源期刊

Canadian Journal of Electrical and Computer Engineering-Revue Canadienne De Genie Electrique et Informatique 工程技术-工程：电子与电气

自引率

0.00%

发文量

期刊介绍： The Canadian Journal of Electrical and Computer Engineering (ISSN-0840-8688), issued quarterly, has been publishing high-quality refereed scientific papers in all areas of electrical and computer engineering since 1976