东南大学学报（英文版）2016，Vol.32Issue(2)：158-163,6.DOI:10.3969/j.issn.1003-7985.2016.02.005
一种新的结合情感数据场和蚁群策略的语音情感识别算法
A novel speech emotion recognition algorithm based on combination of emotion data field and ant colony search strategy
摘要
Abstract
In order to effectively conduct emotion recognition from spontaneous, non-prototypical and unsegmented speech so as to create a more natural human-machine interaction; a novel speech emotion recognition algorithm based on the combination of the emotional data field ( EDF ) and the ant colony search ( ACS ) strategy, called the EDF-ACS algorithm, is proposed. More specifically, the inter-relationship among the turn-based acoustic feature vectors of different labels are established by using the potential function in the EDF. To perform the spontaneous speech emotion recognition, the artificial colony is used to mimic the turn-based acoustic feature vectors. Then, the canonical ACS strategy is used to investigate the movement direction of each artificial ant in the EDF, which is regarded as the emotional label of the corresponding turn-based acoustic feature vector. The proposed EDF-ACS algorithm is evaluated on the continueous audio/visual emotion challenge ( AVEC ) 2012 dataset, which contains the spontaneous, non-prototypical and unsegmented speech emotion data. The experimental results show that the proposed EDF-ACS algorithm outperforms the existing state-of-the-art algorithm in turn-based speech emotion recognition.关键词
语音情感识别/情感数据场/蚁群搜索/人机交互Key words
speech emotion recognition/emotional data field/ant colony search/human-machine interaction分类
信息技术与安全科学引用本文复制引用
查诚,陶华伟,张昕然,周琳,赵力,杨平..一种新的结合情感数据场和蚁群策略的语音情感识别算法[J].东南大学学报（英文版）,2016,32(2):158-163,6.基金项目
The National Natural Science Foundation of China ( No.61231002,61273266,61571106), the Foundation of the Depart-ment of Science and Technology of Guizhou Province ( No.[2015]7637) （ No.61231002,61273266,61571106）
