A Comparison of Evaluation Measures for Emotion Recognition in Dimensional Space

机译：尺寸空间情绪识别评价措施的比较

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Emotion recognition from physiological signals like electroencephalography (EEG) can be performed using different underlying emotion models. While dimensional emotion models have recently gained attention, measures to evaluate recognition methods that are based on these models differ from study to study. This paper offers an analysis of proposed evaluation measures by comparing recognition results achieved on a self recorded dataset. Emotions are estimated using ridge regression and estimation results are compared using different evaluation measures. Additionally, three different baselines are studied, two types of random regression as well as naive estimation. Among the investigated evaluation measures, bandwidth accuracy was found to have many desirable characteristics.

机译：可以使用不同的底层情感模型来执行来自脑电图（EEG）等生理信号的情感识别。虽然尺寸情绪模型最近获得了关注，但评估基于这些模型的识别方法的措施与学习的研究不同。本文通过比较自记录数据集实现的识别结果，提供了对提出的评估措施的分析。使用脊回归估计的情绪，并使用不同的评估措施进行比较估计结果。另外，研究了三种不同的基线，两种类型的随机回归以及天真估计。在调查的评估措施中，发现带宽精度具有许多所需的特征。

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《Humaine Association Conference on Affective Computing and Intelligent Interaction》|2013年||共5页
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Jenke Robert; Peer Angelika; Buss Martin;
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中图分类计算复杂性理论;
关键词
aBCI; dimensional model; emotion Recognition; evaluation measures;

机译：ABCI;尺寸模型;情绪识别;评估措施;

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A Comparison of Evaluation Measures for Emotion Recognition in Dimensional Space

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