Identification and Classification of Chinese Traditional Musical Instruments Based on Deep Learning Algorithm

P. Cao
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引用次数: 1

Abstract

The classification of musical instruments based on deep learning is the application of deep learning in the direction of music information retrieval, which is a hot topic in the field of speech recognition in recent years. Deep learning is an important branch of artificial intelligence and a new direction of data mining in recent years. Deep learning is born from artificial neural networks. It has more hidden layers than shallow neural networks. This is the origin of the word "depth ". Unlike traditional neural networks, deep learning increases unsupervised learning. Therefore, this paper studies whether we can use the powerful feature extraction ability of deep learning to study the classification algorithm of music genre recognition based on deep confidence network for the recognition and classification of music genres and traditional Chinese musical instruments. The experimental results show that the accuracy of the algorithm is as high as 99.2.
基于深度学习算法的中国传统乐器识别与分类
基于深度学习的乐器分类是深度学习在音乐信息检索方向上的应用,是近年来语音识别领域的热门话题。深度学习是人工智能的一个重要分支,也是近年来数据挖掘的一个新方向。深度学习源于人工神经网络。它比浅层神经网络有更多的隐藏层。这就是“深度”这个词的由来。与传统的神经网络不同,深度学习增加了无监督学习。因此,本文研究是否可以利用深度学习强大的特征提取能力,研究基于深度置信度网络的音乐体裁识别分类算法,用于音乐体裁和中国传统乐器的识别分类。实验结果表明,该算法的准确率高达99.2。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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