Audio-visual emotion recognition in adult attachment interview

Zhihong Zeng · Yuxiao Hu · Thomas S. Huang · Glenn I. Roisman · Zhen Wen

46 citations0/0 files storedINTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION

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Emotion and Mood Recognition Speech Recognition and Synthesis Speech and Audio Processing

Abstract

Automatic multimodal recognition of spontaneous affective expressions is a largely unexplored and challenging problem. In this paper, we explore audio-visual emotion recognition in a realistic human conversation setting - Adult Attachment Interview (AAI). Based on the assumption that facial expression and vocal expression be at the same coarse affective states, positive and negative emotion sequences are labeled according to Facial Action Coding System Emotion Codes. Facial texture in visual channel and prosody in audio channel are integrated in the framework of Adaboost multi-stream hidden Markov model (AMHMM) in which Adaboost learning scheme is used to build component HMM fusion. Our approach is evaluated in the preliminary AAI spontaneous emotion recognition experiments.

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1997Affective Computing 1978Facial Action Coding System 2001Emotion recognition in human-computer interaction 2017Communication Without Words 2004Analysis of emotion recognition using facial expressions, speech and multimodal information 2003Toward an affect-sensitive multimodal human-computer interaction 2005Recognizing Facial Expression: Machine Learning and Application to Spontaneous Behavior 2003Describing the emotional states that are expressed in speech

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2012Human emotion and cognition recognition from body language of the head using soft computing techniques 2011Audio Visual Emotion Recognition Based on Triple-Stream Dynamic Bayesian Network Models

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