Study on facial emotional expression induced by the annoying noise

噪声作用下的人脸面部情绪表情研究

¹ School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China
² School of Civil Engineering and Architecture, Zhejiang University of Science and Technology, Hangzhou 310023, China

Received: 21 September 2022

Abstract

Noise is annoying. Facial expressions indicate diverse emotions instantly, objectively and accurately. In this paper, the facial emotional expression is used to assess the noise annoyance to nullify the disadvantages of traditional evaluation methods. Firstly, by exploiting listening experiments, the facial videos, physiological signals and individual annoyance from 30 listeners with different nationalities were collected. Then, the facial action units (AUs) were extracted, identified and analyzed, and the AUs combination reflects annoyed emotion induced by the noise was confirmed. Furthermore, a novel evaluation scale embodying color and emotional symbols was proposed, which has been proven to be valid by the social surveys. The present study confirms that it is feasible to evaluate the noise annoyance more objectively by exploring the listener's facial "annoyance" expression. The innovative scale can avoid the understanding bias and improve the evaluation efficiency remarkably.

摘要

噪声使人烦恼。面部表情能够即时、客观地显现情绪状态。尝试以人在聆听噪声时面部表情特征的变化表征噪声的烦恼度, 以期消除传统主观评价方法的诸多弊端。借助听音实验, 采集了30位不同国籍听音者在聆听不同类型噪声时的面部视频、生理信号和个人烦恼度; 对听音者面部关键动作单元(action units, AUs)进行提取、识别与分析, 确定了听音者因噪声而烦恼时面部情绪表情的AUs组合表达; 创设了融合(灰)色相明度变化的烦恼度评价量表, 经网络调查验证有效。研究证实: 以听音者面部(烦恼)情绪表情的特征变化客观评价噪声烦恼度是可行的; 融入具象化元素的烦恼度评价量表能够有效避免理解偏差, 提高评价效率。