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Low-Level Characterization of Expressive Head Motion Through Frequency Domain Analysis

机译：通过频域分析表现富有效应头动作的低级表征

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摘要

For the purpose of understanding how head motions contribute to the perception of emotion in an utterance, we aim to examine the perception of emotion based on Fourier transform-based static and dynamic features of head motion. Our work is to conduct intra-related objective analysis and perceptual experiments on the link between the perception of emotion and the static/dynamic features. The objective analysis outcome shows that the static and dynamic features are effective in characterizing and recognizing emotions. The perceptual experiments enable us to collect human perception of emotion through head motion. The collected perceptual data shows that humans are unable to reliably perceive emotion from head motion alone but reveals that humans are sensitive to the static feature (in reference to the averaged up-down rotation angle) and the dynamic features (which reflect the fluidity and speed of movement). It also indicates that humans perceive emotion carried in head motion and the naturalness of head motion in two different channels. Our work contributes to the understanding and the characterization of head motion in expressive speech through low-level descriptions of motion features, instead of commonly used high-level motion style (e.g., head nods, shakes, tilts, and raises).
机译：为了了解头部动作如何促进情绪的感知，我们的目标是根据傅立叶变换的静态动态特征来研究情绪的感知。我们的作品是对情绪和静态/动态特征的看法之间的联系进行相关的目标分析和感知实验。目标分析结果表明，静态和动态特征在表征和识别情绪方面都有效。感知实验使我们能够通过头部运动来收集对情感的人类感知。收集的感知数据表明，人类无法单独地从头部运动中可靠地感知，但揭示了人类对静态特征（参考平均上下旋转角度）和动态特征（这反映流动性和速度）敏感运动）。它还表明人类在两种不同通道中感知头部运动和头部运动的自然感知。我们的工作通过运动特征的低级描述来促进致力于言论的理解和表征，而不是常用的高级运动样式（例如，头部点头，摇晃，倾斜和提升）。

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