• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Mathematical Problems in Engineering >A New Fuzzy Cognitive Map Learning Algorithm for Speech Emotion Recognition
【24h】

A New Fuzzy Cognitive Map Learning Algorithm for Speech Emotion Recognition

机译：语音情感识别的模糊认知图学习新算法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Selecting an appropriate recognition method is crucial in speech emotion recognition applications. However, the current methods do not consider the relationship between emotions. Thus, in this study, a speech emotion recognition system based on the fuzzy cognitive map (FCM) approach is constructed. Moreover, a new FCM learning algorithm for speech emotion recognition is proposed. This algorithm includes the use of the pleasure-arousal-dominance emotion scale to calculate the weights between emotions and certain mathematical derivations to determine the network structure. The proposed algorithm can handle a large number of concepts, whereas a typicalFCMcan handle only relatively simple networks (maps). Different acoustic features, including fundamental speech features and a new spectral feature, are extracted to evaluate the performance of the proposed method. Three experiments are conducted in this paper, namely, single feature experiment, feature combination experiment, and comparison between the proposed algorithm and typical networks. All experiments are performed on TYUT2.0 and EMO-DB databases. Results of the feature combination experiments show that the recognition rates of the combination features are 10%-20% better than those of single features. The proposed FCM learning algorithm generates 5%-20% performance improvement compared with traditional classification networks.
机译：在语音情感识别应用中，选择合适的识别方法至关重要。但是，当前的方法没有考虑情绪之间的关系。因此，本研究构建了一种基于模糊认知图（FCM）方法的语音情感识别系统。提出了一种新的语音情感识别的FCM学习算法。该算法包括使用愉悦度主导情绪量表来计算情绪之间的权重以及确定网络结构的某些数学推导。所提出的算法可以处理大量概念，而典型的FCM只能处理相对简单的网络（地图）。提取了不同的声学特征，包括基本语音特征和新的频谱特征，以评估该方法的性能。本文进行了三个实验，即单特征实验，特征组合实验以及所提算法与典型网络的比较。所有实验均在TYUT2.0和EMO-DB数据库上进行。特征组合实验的结果表明，组合特征的识别率比单个特征的识别率高10％-20％。与传统分类网络相比，提出的FCM学习算法可将性能提高5％-20％。

著录项

  • 来源
    《Mathematical Problems in Engineering》 |2017年第7期|4127401.1-4127401.12|共12页
  • 作者

    Zhang Wei; Zhang Xueying; Sun Ying;

  • 作者单位

    Taiyuan Univ Technol, Coll Informat Engn, Taiyuan 030024, Peoples R China;

    Taiyuan Univ Technol, Coll Informat Engn, Taiyuan 030024, Peoples R China;

    Taiyuan Univ Technol, Coll Informat Engn, Taiyuan 030024, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号