论文标题
沉默特征在维度语音情感识别中的影响
The Effect of Silence Feature in Dimensional Speech Emotion Recognition
论文作者
论文摘要
沉默是人类与人类交流的一部分，这可能是人类情感感知的线索。为了通过计算机自动识别情绪，尚不清楚沉默是否有助于确定语音中的人类情绪。本文介绍了对维度情绪识别中使用沉默特征的效果的研究。由于寂静的特征是根据话语提取的，因此我们将沉默特征分组为一组声学特征的高统计功能。结果表明，与其他情绪维度相比，沉默特征影响唤醒维度。从一致性相关系数角度来看，在计算沉默特征计算中的适当选择改善了维度语音情感识别性能的性能。另一方面，该因素的选择不当会通过使用相同的体系结构导致性能下降。
Silence is a part of human-to-human communication, which can be a clue for human emotion perception. For automatic emotion recognition by a computer, it is not clear whether silence is useful to determine human emotion within a speech. This paper presents an investigation of the effect of using silence feature in dimensional emotion recognition. Since the silence feature is extracted per utterance, we grouped the silence feature with high statistical functions from a set of acoustic features. The result reveals that the silence features affect the arousal dimension more than other emotion dimensions. The proper choice of a threshold factor in the calculation of silence feature improved the performance of dimensional speech emotion recognition performance, in terms of a concordance correlation coefficient. On the other side, improper choice of that factor leads to a decrease in performance by using the same architecture.
