ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

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微语调表情:检测情绪泄露的新框架

申寻兵, 丰婷婷, 盛静, 彭咏梅, 刘仪辉, 李雅方, 陈振彩   

  1. 江西中医药大学人文学院, 江西 330004 中国
    江西省中医药管理局中医心理与脑科学重点研究室, 江西 330004 中国
  • 收稿日期:2026-02-03 修回日期:2026-02-11 接受日期:2026-04-08
  • 基金资助:
    国家自然科学基金(微语调表情与欺骗检测)(32560200); 教育部人文社会科学研究规划基金项目(基于语调表情的欺骗检测)(24YJA190013)

Vocal micro-expressions: A new framework for detecting of emotional leakage

Shen Xunbing, Feng Tingting, Sheng Jing, Peng Yongmei, Liu Yihui, Li Yafang, Chen Zhencai   

  1. School of Humanities, Jiangxi University of Chinese Medicine 330004, China
    , Key Laboratory of Psychology of TCM and Brain Science, Jiangxi Administration of Traditional Chinese Medicine 330004, China
  • Received:2026-02-03 Revised:2026-02-11 Accepted:2026-04-08
  • Supported by:
    The National Natural Science Foundation of China(Vocal Micro-expressions and Deception Detection)(32560200); Ministry of Education Humanities and Social Sciences Research Planning Fund Project(Deception detection based on vocal expressions)(24YJA190013)

摘要: 微表情是一种泄露出来的反映内心真实情绪状态的短暂表情,已有文献对微表情的研究主要集中在微面部表情上,微表情的发现和定义也只提及了面部表情。那么,在语调表情中是否也存在类似的情绪泄露,即是否存在微语调表情?各种证据表明微语调表情是存在的:生活中,人们可以听出他人在说话时的紧张与不安;理论上,压抑的情绪可以通过语音通道泄露出来。泄露出来的微语调表情如何捕捉?听觉上微语调表情可能较难被觉察,但可以通过言语情绪识别技术,借鉴物理学的应变(Strain)概念,对语音中泄露出来的短暂情绪信息进行客观度量;同时,通过系列心理学实验分析这些短暂情绪信息的特征并将其应用到欺骗检测中,为微语调表情的存在提供科学证据。本研究从理论建构的角度分析微语调表情概念的内涵和外延、结构和功能,将深化对微表情的理论认识及促进其在欺骗检测中的应用。

关键词: 微语调表情, 情绪泄露, 言语情绪识别, 欺骗检测, 机器学习

Abstract: A micro-expression is a brief, involuntary expression that leaks out and reflects an individual’s genuine internal emotional state. Existing research on micro-expressions has primarily focused on micro facial expressions, and the discovery and definition of micro-expressions have been confined to the face. This raises an important question: does a similar form of emotional leakage occur in vocal prosody—that is, do vocal micro-expressions exist? Converging evidence suggests that such vocal micro-expressions do exist. In everyday life, listeners are often able to perceive tension and anxiety in others’ speech; theoretically, suppressed emotions may also leak through the vocal channel. How, then, can these leaked vocal micro-expressions be captured? Although vocal micro-expressions may be difficult to consciously detect through auditory perception alone, they can be objectively quantified using speech emotion recognition techniques by drawing on the physical concept of strain to measure transient emotional information leaked in speech. In addition, a series of psychological experiments can be conducted to analyze the characteristics of these transient emotional signals and apply them to deception detection, thereby providing scientific evidence for the existence of vocal micro-expressions. From the perspective of theoretical construction, the present study examines the connotation and extension, structure, and function of the concept of vocal micro-expressions, with the aim of deepening theoretical understanding of micro-expressions and facilitating their use in deception detection.

Key words: vocal micro-expressions, leakage of emotion, speech emotion recognition, deception detection, machine learning