Livingstone Steven R, Palmer Caroline
Department of Psychology, McGill University.
Emotion. 2016 Apr;16(3):365-80. doi: 10.1037/emo0000106. Epub 2015 Oct 26.
When speaking or singing, vocalists often move their heads in an expressive fashion, yet the influence of emotion on vocalists' head motion is unknown. Using a comparative speech/song task, we examined whether vocalists' intended emotions influence head movements and whether those movements influence the perceived emotion. In Experiment 1, vocalists were recorded with motion capture while speaking and singing each statement with different emotional intentions (very happy, happy, neutral, sad, very sad). Functional data analyses showed that head movements differed in translational and rotational displacement across emotional intentions, yet were similar across speech and song, transcending differences in F0 (varied freely in speech, fixed in song) and lexical variability. Head motion specific to emotional state occurred before and after vocalizations, as well as during sound production, confirming that some aspects of movement were not simply a by-product of sound production. In Experiment 2, observers accurately identified vocalists' intended emotion on the basis of silent, face-occluded videos of head movements during speech and song. These results provide the first evidence that head movements encode a vocalist's emotional intent and that observers decode emotional information from these movements. We discuss implications for models of head motion during vocalizations and applied outcomes in social robotics and automated emotion recognition.
在说话或唱歌时,歌手常常会以富有表现力的方式移动头部,但情感对歌手头部动作的影响尚不清楚。通过一项比较性的言语/歌曲任务,我们研究了歌手的情感意图是否会影响头部动作,以及这些动作是否会影响所感知到的情感。在实验1中,我们使用动作捕捉技术记录歌手在以不同情感意图(非常高兴、高兴、中性、悲伤、非常悲伤)说出和唱出每条语句时的情况。功能数据分析表明,头部动作在不同情感意图下的平移和旋转位移有所不同,但在言语和歌曲中却相似,超越了基频(言语中自由变化,歌曲中固定)和词汇变化的差异。特定于情感状态的头部动作发生在发声之前和之后,以及发声过程中,这证实了动作的某些方面并非仅仅是发声的副产品。在实验2中,观察者能够根据歌手在言语和歌曲过程中头部动作的无声、面部遮挡视频准确识别出他们的情感意图。这些结果首次证明,头部动作编码了歌手的情感意图,并且观察者能够从这些动作中解码情感信息。我们讨论了这些结果对发声过程中头部动作模型的影响以及在社交机器人技术和自动情感识别中的应用成果。