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Automatic Music Genre Detection Using Artificial Neural Networks

机译:使用人工神经网络自动音乐类型检测

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In this paper, we have explored the use of artificial neural networks (ANNs) for automatically detecting the genre of music. The challenge faced when hand-classifying music is that it is highly dependent on the accuracy and experience of the person classifying it. The main objective of this paper is to build an arrangement which will reduce the burden and increase the accuracy of classifying the genre of music. We use MFCC as feature vectors and use multilayer perceptrons (MLPs) to classify the data into the various genres. We have trained our model on a novel dataset that reflects current trends in music and addresses the problems faced with existing datasets.
机译:在本文中,我们探索了使用人工神经网络(ANNS)来自动检测音乐类型。 当手工分类音乐是它高度依赖于分类它的人的准确性和经验时面临的挑战。 本文的主要目标是建立一个安排,这将减少负担并提高分类音乐类型的准确性。 我们使用MFCC作为特征向量,并使用多层的感知(MLP)将数据分类为各种类型。 我们在新型数据集上培训了我们的模型,反映了音乐的当前趋势,并解决了现有数据集面临的问题。

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