تقرير
MERGE -- A Bimodal Dataset for Static Music Emotion Recognition
| العنوان: | MERGE -- A Bimodal Dataset for Static Music Emotion Recognition |
|---|---|
| المؤلفون: | Louro, Pedro Lima, Redinho, Hugo, Santos, Ricardo, Malheiro, Ricardo, Panda, Renato, Paiva, Rui Pedro |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Sound, Computer Science - Information Retrieval, Computer Science - Machine Learning, Computer Science - Multimedia, Electrical Engineering and Systems Science - Audio and Speech Processing |
| الوصف: | The Music Emotion Recognition (MER) field has seen steady developments in recent years, with contributions from feature engineering, machine learning, and deep learning. The landscape has also shifted from audio-centric systems to bimodal ensembles that combine audio and lyrics. However, a severe lack of public and sizeable bimodal databases has hampered the development and improvement of bimodal audio-lyrics systems. This article proposes three new audio, lyrics, and bimodal MER research datasets, collectively called MERGE, created using a semi-automatic approach. To comprehensively assess the proposed datasets and establish a baseline for benchmarking, we conducted several experiments for each modality, using feature engineering, machine learning, and deep learning methodologies. In addition, we propose and validate fixed train-validate-test splits. The obtained results confirm the viability of the proposed datasets, achieving the best overall result of 79.21% F1-score for bimodal classification using a deep neural network. Comment: 16 pages, 4 figures, 13 tables, submitted to IEEE Transactions on Affective Computing |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2407.06060 |
| رقم الأكسشن: | edsarx.2407.06060 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |