Using Convolutional Neural Networks for Music Emotion Recognition on Microcontrollers

2023 IEEE 64th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2023): Proceedings 2023
Laima Kamzola, Alla Anohina-Naumeca

This paper presents a theoretical overview of music emotion recognition (MER) and its processes. More than 30 studies related to emotion recognition and MER were analyzed. Summaries of information about emotion recognition methods, available audio datasets, and audio parameters used in MER are discussed in this paper. The practical part is focused on a proof of concept for MER using the Convolutional Neural Network model on microcontrollers for realtime music emotion classification in four emotion classes based on a 2D emotion model.

Keywords
audio datasets | audio parameters | convolutional neural networks | emotion recognition methods | microcontrollers | music emotion recognition
DOI
10.1109/ITMS59786.2023.10317771
Hyperlink
https://ieeexplore.ieee.org/document/10317771

Kamzola, L., Anohina-Naumeca, A. Using Convolutional Neural Networks for Music Emotion Recognition on Microcontrollers. In: 2023 IEEE 64th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2023): Proceedings, Latvia, Riga, 5-6 October, 2023. Piscataway: IEEE, 2023, pp.1-6. ISBN 979-8-3503-7030-0. e-ISBN 979-8-3503-7029-4. ISSN 2771-6953. e-ISSN 2771-6937. Available from: doi:10.1109/ITMS59786.2023.10317771

Publication language
English (en)