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Deep Learning-Enhanced Emotion-Based Music System with Age and Language Personalization

Publication Type : Conference Paper

Publisher : IEEE

Source : 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)

Url : https://doi.org/10.1109/ICCCNT61001.2024.10724342

Campus : Bengaluru

School : School of Computing

Year : 2024

Abstract : Music plays an important role in understanding human mood, and the facial expressions acts as a quick way of non-linguistic communication. The emotion-based music playing system provide users with options to choose his/her preferred age and language. Uses deep learning techniques and detects seven emotions from a person’s face using a web camera. Based on the three aspects age, language, and detected emotion the song playlists are recommended. A Convolutional Neural Network (CNN) model is trained on a dataset to achieve the accurate emotion detection. The designed System allows the users to interact with website and view their identified emotions ensuring enhanced user experience.

Cite this Research Publication : Trisha, Kariveda, Padigela Srinithya Reddy, Nichenametla Hima Sree, Tripty Singh, and Mansi Sharma. "Deep Learning-Enhanced Emotion-Based Music System with Age and Language Personalization." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), pp. 1-7. IEEE, 2024.

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