数据采集与处理2016，Vol.31Issue(2)：325-330,6.DOI:10.16337/j.1004-9037.2016.02.012
基于稀疏特征迁移的语音情感识别
Speech Emotion Recognition Using Sparse Feature Transfer
摘要
Abstract
In speech emotion recognition system ,recognition rates will drop drastically when the training and the testing utterances are from different corpora .To solve this problem ,a novel sparse feature trans‐fer approach is proposed .By employing sparse coding algorithm ,the common sparse feature representa‐tion of emotion features from different corpora is obtained .Meanwhile ,the maximum mean discrepancy (MMD) algorithm is introduced to measure the distance between different distributions ,and is used as the regularization term for the objective function of sparse coding .Finally ,the robust sparse features are achieved for recognition .Experimental results show that ,compared to traditional methods ,the proposed approach can significantly improve the recognition rates for cross databases .关键词
语音情感识别/特征迁移/稀疏编码Key words
speech emotion recognition/feature transfer/sparse coding分类
信息技术与安全科学引用本文复制引用
宋鹏,金赟,查诚,赵力..基于稀疏特征迁移的语音情感识别[J].数据采集与处理,2016,31(2):325-330,6.基金项目
山东省自然科学基金（ZR2014FQ016，ZR2015PF010）资助项目；国家自然科学基金（61273266，61403328，61403329）资助项目；东南大学基本科研业务费（CDLS-2015-04）资助项目。 （）
