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首页> 外文会议>International Conference on Affective Computing and Intelligent Interaction >Cross-corpus acoustic emotion recognition: Variances and strategies (Extended abstract)
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Cross-corpus acoustic emotion recognition: Variances and strategies (Extended abstract)

机译：交叉语料库声学情感识别：差异和策略（扩展摘要）

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摘要

As the recognition of emotion from speech has matured to a degree where it becomes applicable in real-life settings, it is time for a realistic view on obtainable performances. Most studies tend to overestimation in this respect: acted data is often used rather than spontaneous data, results are reported on pre-selected prototypical data, and true speaker disjunctive partitioning is still less common than simple cross-validation. A considerably more realistic impression can be gathered by inter-set evaluation: we therefore show results employing six standard databases in a cross-corpora evaluation experiment. To better cope with the observed high variances, different types of normalization are investigated. 1.8 k individual evaluations in total indicate the crucial performance inferiority of inter- to intra-corpus testing.
机译：由于对来自语音的情感的识别已经成熟，因此在实际设置中适用的程度，是时候了解可获得的表演的真实性观点。大多数研究倾向于在这方面倾向于高估：常用的数据通常使用而不是自发的数据，结果是在预先选择的原型数据上报告的，而真正的扬声器脱位分区仍然不太常见，而不是简单的交叉验证。可以通过跨跨越式评估来收集相当多的现实印象：因此，我们将在跨学院评估实验中显示采用六个标准数据库的结果。为了更好地应对观察到的高差异，研究了不同类型的归一化。 1.8 K总数的各个评估表明了对语料库内测试的至关重要的效率。

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