Emotion Echo:Music That Resonates Your Mood

DOI

10.2991/978-94-6463-858-5_66How to use a DOI?

Keywords

Emotion; algorithms; detection; python; API

Abstract

In today’s digital music platforms, recommendation algorithms are primarily static, relying on historical user data and past listening habits to suggest content. These systems often fail to address users’ dynamic emotional needs, leading to a disconnect between the recommended music and the user’s current emotional state, which diminishes user satisfaction and engagement. To overcome this limitation, we propose, a real-time emotion- based music recommendation. Emotion echo integrates emotion detection technology using Face API for facial expression recognition, which classifies user emotions into categories such as happy, sad, neutral, and angry. The emotion detection module is built using Python and Face API.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ravindranath Gatte
AU  - Talla Manikanta
AU  - Surala Pavan Kumar
AU  - Chintada Manohar
AU  - Singavarapu Venkata Vishnu
PY  - 2025
DA  - 2025/11/04
TI  - Emotion Echo:Music That Resonates Your Mood
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 773
EP  - 784
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_66
DO  - 10.2991/978-94-6463-858-5_66
ID  - Gatte2025
ER  -