Speech emotion recognition for SROL database using weighted KNN algorithm

Monica Feraru, M. Zbancioc
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引用次数: 15

Abstract

In this study, we utilized an improved version of the classical KNN algorithm which associates to each parameter from the features vectors weights according to their performance in the classification process. We obtained the recognition percents of emotions around 65-67%, for the Romanian language, on the SROL database, which are comparable with the results for other languages, with non-professional voice database. This is the first study when the parameters are extracted on the sentence level. Until now, the analysis was made on the phoneme level.
基于加权KNN算法的SROL数据库语音情感识别
在本研究中,我们使用了经典KNN算法的改进版本,该算法根据特征向量在分类过程中的表现与每个参数的权重相关联。在SROL数据库中,我们获得了罗马尼亚语的情绪识别率约为65-67%,这与非专业语音数据库中其他语言的结果相当。这是第一个在句子层面提取参数的研究。到目前为止,分析都是在音素水平上进行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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