Application of artificial intelligence CNN model in emotional recognition of instrumental music
Yang Liu · 2025
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Description
Yang Liu, writing alone in twenty twenty-five, built a neural network that reads emotion in instrumental music. Knowing what a piece feels like powers recommendation and media tagging. The proposed model stacks three components. A convolutional network extracts local emotional features from audio. A bidirectional recurrent unit then models how those features evolve over time, in both directions. An attention mechanism finally spotlights the most emotionally telling segments.
Low-level audio features and high-level semantic features are fused at several scales during extraction. Validation used three datasets, including two public collections and a large emotion-annotated music database. The design aims at accuracy plus generalization across collections. Liu's architecture treats musical emotion as something that builds and shifts across a track, not a single static label.
Catalog record
| CREATOR | Yang Liu |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 65 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |