计算机工程与应用2013，Vol.49Issue(3)：152-155,4.DOI:10.3778/j.issn.1002-8331.1107-0127
基于混合特征参数和BP_Adaboost的方言辨识
Chinese dialects identification based on mixed characteristic parameters and BP_Adaboost
摘要
Abstract
A kind of model combining the BP neural network with the Adaboost is proposed to identify isolated words of Hunan dialect speaker-independently in this paper. In order to reflect the dynamic properties of dialects and the characteristics of vocal tract, LPCC, MFCC and their first-order differential coefficients are combined together as dialects characteristic coefficients. Multiple BP neural networks are used as weak classifiers for dialect initial identification, and then a strong classifier is constructed from these weak classifiers based on Adaboost iteration algorithm to obtain the final identification results. The experimental results show that this hybrid model has stronger robustness and higher recognition rate than the pure BP neural network under relatively low signal to noise ratio.关键词
方言辨识/混合特征参数/自适应Boosting/反向传播(BP)神经网络Key words
dialects identification/ mixed characteristic parameters/ auto-adapted Boosting/ Back Propagation (BP) neural network分类
信息技术与安全科学引用本文复制引用
彭湘陵,钱盛友,赵新民..基于混合特征参数和BP_Adaboost的方言辨识[J].计算机工程与应用,2013,49(3):152-155,4.基金项目
国家自然科学基金(No.11174077) （No.11174077）
湖南省自然科学基金(No.11JJ3079) （No.11JJ3079）
湖南省教育厅资助科研项目(No.11C0844). （No.11C0844）
