Feature Analysis and Application of Music Works Based on Artificial Neural Network
e
27 feb 2025
INFORMAZIONI SU QUESTO ARTICOLO
Pubblicato online: 27 feb 2025
Ricevuto: 04 ott 2024
Accettato: 26 gen 2025
DOI: https://doi.org/10.2478/amns-2025-0130
Parole chiave
© 2025 Yu Wang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Figure 1.
Figure 2.
Figure 3.
Figure 4.
Figure 5.
Figure 6.
Figure 7.
Figure 8.
Figure 9.
characteristics
| Feature number | Feature name | Characteristic dimension |
|---|---|---|
| 1 | zero crossing rate | 1 |
| 2 | root mean square | 1 |
| 3 | spectral centroid | 1 |
| 4 | spectralroll-off frequency | 1 |
| 5 | spectral contrast | 7 |
| 6 | MFCC | 12 |
experimental results
| structure | Rnet1 | Rnet2 | Rnet3 | Rnet4 | Rnet5 |
|---|---|---|---|---|---|
| Circulation layer (128) | ✓ | ✓ | ✓ | ✓ | ✓ |
| Circulation layer (128) | ✓ | ✓ | ✓ | ✓ | |
| Circulation layer (128) | ✓ | ✓ | ✓ | ||
| Circulation layer (128) | ✓ | ✓ | |||
| Circulation layer (128) | ✓ | ||||
| Pooling | Last | Last | Last | Last | Last |
| Full connection (256) | ReLU | ReLU | ReLU | ReLU | ReLU |
| Full connection (256) | ReLU | ReLU | ReLU | ReLU | ReLU |
| Full connection (10/6) | Softmax | Softmax | Softmax | Softmax | Softmax |
data set table
| data set | GTAZN | ISMIR2022 |
|---|---|---|
| Rnetl | 78.32% | 78.41% |
| Rnet2 | 79.67% | 79.53% |
| Rnet3 | 80.14 | 81.22% |
| Rnet4 | 79.09% | 81.30 |
| Rnet5 | 77.73% | 78.05% |