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Machine Learning and Emotions: The Hidden Language in Your Voice
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Author(s): Jesús Heriberto Orduño-Osuna (Universidad Politécnica de Baja California, Mexico), María E. Raygoza L. (Universidad Politécnica de Baja California, Mexico), Roxana Jiménez-Sánchez (Universidad Politécnica de Baja California, Mexico), Guillermo M. Limón-Molina (Universidad Politécnica de Baja California, Mexico)and Fabian N. Murrieta-Rico (Universidad Politécnica de Baja California, Mexico)
Copyright: 2024
Pages: 23
Source title:
Machine and Deep Learning Techniques for Emotion Detection
Source Author(s)/Editor(s): Mritunjay Rai (Department of Electrical and Electronics Engineering, Shri Ramswaroop Memorial University, India)and Jay Kumar Pandey (Department of Electrical and Electronics Engineering, Shri Ramswaroop Memorial University, India)
DOI: 10.4018/979-8-3693-4143-8.ch001
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Abstract
This chapter immerses the reader in the world of emotion recognition, revealing its revolutionary potential through machine learning techniques. From affective computing to sentiment analysis, human-computer interaction to healthcare, this technology has a vast array of practical uses. This journey, therefore, sets out to explore the many possibilities and obstacles in the progression of emotion recognition. Key areas include cross-cultural sensitivity, context-specific recognition, ethical concerns, developing a comprehensive emotional taxonomy, real-time capabilities, and the incorporation of multiple modes of detection. The chapter provides insights into future research opportunities, underscoring the importance of culturally sensitive, ethically sound, and comprehensive emotion recognition systems. By addressing these considerations, this chapter looks to contribute to the ongoing evolution of machine learning and emotions, laying the foundation for more robust and diverse real-world applications.
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