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Context-based emotion recognition: A survey
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AI
DOI：10.1016/j.neucom.2024.129073.png)
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Abstract
En 中文
Emotions playa crucial role inhuman communication, and accurately recognizing them is essential for developing intelligent systems capable of effective human-computer interaction. Contextual information, including body language, tone of voice, situational cues, and facial expressions, significantly influences the analysis of emotions. This survey paper investigates the critical role of context in emotion recognition and comprehensively analyzes the various techniques employed in Context-Based Emotion Recognition (CBER). It highlights the associated challenges and limitations, examines the datasets used in emotion recognition research, and discusses the performance evaluation metrics utilized to assess the accuracy and effectiveness of algorithms and models in understanding emotions within their respective contexts. Furthermore, the paper explores practical applications of context-based emotion recognition across diverse fields. It serves as an invaluable resource for researchers seeking insights into the latest developments in this field and identifies future research directions to advance context-based emotion recognition.
Keywords:
Emotion recognition
Contextual information
Emotion detection techniques
Real-life applications
Journal
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6.5
Papers:
2.5W
Citations:
6.5W