Emotion Recognition in AI: Bridging Human Expressions and Machine Learning

Author(s)	Vaibhav Jindal, Ketak Singh
Country	India
Abstract	Emotion recognition in artificial intelligence represents a critical advancement in human-machine interaction, bridging the gap between computational capabilities and human emotional expression. This paper examines the current state of emotion recognition technologies, including facial expression analysis, speech pattern recognition, physiological signal processing, and multimodal approaches. It analyzes public attitudes in India regarding emotional intelligence and AI integration, highlighting both optimism for technological advancement and concerns about privacy and ethical implications. The study explores various applications across healthcare, education, customer service, and human-robot interaction, while addressing key challenges in cultural diversity, data privacy, and system reliability. Future directions emphasize the need for context-aware, culturally sensitive systems that balance technological innovation with ethical considerations.
Keywords	Emotion Recognition, Artificial Intelligence, Human-Machine Interaction, Emotional Intelligence, Privacy and Ethics
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 1, January-February 2025
Published On	2025-01-07
Cite This	Emotion Recognition in AI: Bridging Human Expressions and Machine Learning - Vaibhav Jindal, Ketak Singh - IJFMR Volume 7, Issue 1, January-February 2025.

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