musi-ABC for Predicting Musical Emotions

• Published in: IEEE access Vol. 11; p. 1
• Main Author: Yang, Jing
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Ablation; Accuracy; Artificial neural networks; Benchmarks; Complete critical points; Convolutional neural networks; Data mining; Deep learning; Efficiency; Emotion recognition; Emotions; Feature extraction; Long term dependency; Modules; Music; Neural networks; Outliers (statistics); Partial critical features; Predicting musical emotions; Prediction models; Predictions; Predictive models; Recurrent neural networks; Training

To address the issues of insufficient accuracy and low training efficiency in general musical emotion prediction models, we propose the muSi-ABC architecture for predicting music emotions. Specifically, in the feature extraction stage of music emotions, we use a benchmark feature set to ensure that...