摘要
研究了一种常用的模式分类器——BP神经网络,分析了BP网络的训练及识别过程,提取了能体现声调特性的特征数据组成分类特征向量,设计了具有一个隐含层的3层前馈网络作为分类器,对普通话声调样本库做了分类识别实验,分析了不同隐含层节点数的识别实验结果.实验结果表明,提取的音频特征基本有效,分类效果良好,具有一定的应用价值.
The BP neural network is studied and applied to tone recognition in this paper, which is a frequently used pattern classifier. Based on analysis of training and recognition processes of BP neural network, we extract feature data reflecting the tone characteristics to build the classification eigenvector. The classifier is designed as a 3- layer BP neural network with one hidden layer, and applied to recognize the four tones of Mandarin Chinese. The recognition results by BP neural network with different hidden layer nodes are compared. The experiment result indicates that the audio feature extracted by this classifier is valid for Mandarin Chinese, and verifies its good classification performance.
出处
《南京信息工程大学学报(自然科学版)》
CAS
2012年第5期456-460,共5页
Journal of Nanjing University of Information Science & Technology(Natural Science Edition)
基金
2010年江苏省政府留学奖学金项目
江苏省教育科学"十二五"规划课题(C-C/2011/01/42)
南京信息工程大学教学建设与改革工程项目(11JY056)
南京信息工程大学高等教育调研及政策研究课题(2012GJ002)
南京信息工程大学实验室开放项目(12KF034
12KF028)
关键词
BP网络
音频特征分析
声调识别
back-propagation neural network
audio feature extraction
tone recognition