全世界有16種面部表情出現在相似背景中
作者:
小柯機器人發布時間:2020/12/18 21:25:24
美國加州大學伯克利分校Alan S. Cowen研究組取得一項新突破。他們的論文發現了全世界有16種面部表情出現在相似的背景中。相關論文發表在2020年12月16日出版的《自然》雜誌上。
通過將機器學習方法應用於現實世界中的動態行為,他們可以確定自然主義的社交環境(例如婚禮或體育比賽)是否與跨不同文化的特定面部表情相關聯。在兩個使用深度神經網絡的實驗中,他們檢查了來自144個國家/地區的600萬個視頻中數千種情況下16種類型的面部表情系統發生的程度。
他們發現,每種面部表情都與一組背景有獨特的關聯,這些背景在12個世界區域中保留了70%。與這些關聯相一致,不同背景下面部表情最顯著的結果是產生不同面部表情的頻率各不相同。他們的結果揭示了在整個現代世界中保留下來的人類面部表情的細粒度模式。
據了解,了解人的面部表情與各種文化中特定社會背景的變化程度,對於情感能夠對重要的挑戰和機遇做出適應性反應至關重要。將社會背景與特定面部表情相關聯的具體證據很少,並且很大程度上基於基於調查的方法,這些方法通常受到語言和小樣本量的限制。
附:英文原文
Title: Sixteen facial expressions occur in similar contexts worldwide
Author: Alan S. Cowen, Dacher Keltner, Florian Schroff, Brendan Jou, Hartwig Adam, Gautam Prasad
Issue&Volume: 2020-12-16
Abstract: Understanding the degree to which human facial expressions co-vary with specific social contexts across cultures is central to the theory that emotions enable adaptive responses to important challenges and opportunities1,2,3,4,5,6. Concrete evidence linking social context to specific facial expressions is sparse and is largely based on survey-based approaches, which are often constrained by language and small sample sizes7,8,9,10,11,12,13. Here, by applying machine-learning methods to real-world, dynamic behaviour, we ascertain whether naturalistic social contexts (for example, weddings or sporting competitions) are associated with specific facial expressions14 across different cultures. In two experiments using deep neural networks, we examined the extent to which 16 types of facial expression occurred systematically in thousands of contexts in 6 million videos from 144 countries. We found that each kind of facial expression had distinct associations with a set of contexts that were 70% preserved across 12 world regions. Consistent with these associations, regions varied in how frequently different facial expressions were produced as a function of which contexts were most salient. Our results reveal fine-grained patterns in human facial expressions that are preserved across the modern world.
DOI: 10.1038/s41586-020-3037-7
Source: https://www.nature.com/articles/s41586-020-3037-7