Semi-Coupled Hidden Markov Model with State-Based Alignment Strategy for Audio-Visual Emotion Recognition
作者： Jen-Chun Lin , Chung-Hsien Wu , Wen-Li Wei
DOI: 10.1007/978-3-642-24600-5_22
关键词:
摘要: This paper presents an approach to bi-modal emotion recognition based on a semi-coupled hidden Markov model (SC-HMM). A simplified state-based alignment strategy in SC-HMM is proposed align the temporal relation of states between audio and visual streams. Based this strategy, can alleviate problem data sparseness achieve better statistical dependency HMMs most real world scenarios. For performance evaluation, audio-visual signals with four emotional (happy, neutral, angry sad) were collected. Each invited seven subjects was asked utter 30 types sentences twice generate speech facial expression for each emotion. Experimental results show outperforms other fusion-based methods.
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