摘要
针对单一特征难以建立理想音乐分类模型的不足,为了帮助用户找到自己喜欢的音乐,提出BP神经网络的音乐分类模型。首先提取音乐的多种类型特征,便于对音乐信息进行准确描述,然后将这些特征组合在一起作为音乐分类模型的输入向量,通过BP神经网络的智能学习建立音乐分类模型,最后在Matlab 2016平台下进行多个音乐分类实验。结果表明,该模型克服了单一特征提供信息简单的局限性,提高了音乐的分类正确率,而且音乐分类的实时性较好,可以用于网络上的音乐检索研究。
Since the use of single feature is difficult to establish the satisfied music classification model,a music classification model based on BP neural network is proposed to help users to find their favorite music. The music characteristics with multiple types are extracted to describe the music information accurately. The characteristics are combined as the input vector of the music classification model,and the intelligent learning of BP neural network is adopted to establish the music classification model.The multi-music classification experiment was carried out on Matlab 2016 platform. The results show that the model can overcome the limitations of the single feature providing simple information,improve the classification accuracy of the music,has perfect real-time performance of music classification,and is used to study the music retrieval on the network.
出处
《现代电子技术》
北大核心
2018年第5期136-139,共4页
Modern Electronics Technique
关键词
情感特征
音频特征
RBF神经网络
音乐分类器
音乐检索
智能学习
emotion characteristic
audio characteristic
RBF neural network
music classifier
music retrieval
intelligent learning
