Research Article
Feature Aggregation with Two-Layer Ensemble Framework for Multilingual Speech Emotion Recognition
Table 9
Preclassifier RA results for seven emotions using HDFM as training dataset and English IEMOCAP dataset as testing dataset.
| | Precision | Recall | F1-score |
| LRC | | | | Anger | 0.34 | 0.62 | 0.44 | Disgust | 0.39 | 0.41 | 0.40 | Fear | 0.00 | 0.00 | 0.00 | Happiness | 0.22 | 0.06 | 0.10 | Neutral | 0.44 | 0.02 | 0.04 | Sadness | 0.35 | 0.61 | 0.45 | Surprise | 0.04 | 0.14 | 0.06 |
| Accuracy | | | 0.32 |
| Macro Average | 0.18 | 0.19 | 0.13 | Weighted Average | 0.28 | 0.20 | 0.18 |
| RFC | | | | Anger | 0.19 | 0.80 | 0.30 | Disgust | 0.33 | 0.12 | 0.17 | Fear | 0.00 | 0.00 | 0.00 | Happiness | 0.08 | 0.19 | 0.11 | Neutral | 0.27 | 0.10 | 0.15 | Sadness | 0.41 | 0.14 | 0.20 | Surprise | 0.00 | 0.00 | 0.00 |
| Accuracy | | | 0.20 |
| Macro Average | 0.18 | 0.19 | 0.13 | Weighted Average | 0.28 | 0.20 | 0.18 |
| GBC | | | | Anger | 0.00 | 0.00 | 0.00 | Disgust | 0.36 | 0.44 | 0.39 | Fear | 0.25 | 1.00 | 0.40 | Happiness | 0.14 | 0.21 | 0.17 | Neutral | 0.25 | 0.16 | 0.19 | Sadness | 0.43 | 0.14 | 0.21 | Surprise | 0.00 | 0.00 | 0.00 |
| Accuracy | | | 0.24 |
| Macro Average | 0.20 | 0.28 | 0.20 | Weighted Average | 0.27 | 0.24 | 0.24 |
| MLP-C | | | | Anger | 0.23 | 0.34 | 0.28 | Disgust | 0.31 | 0.21 | 0.25 | Fear | 0.00 | 0.00 | 0.00 | Happiness | 0.09 | 0.20 | 0.12 | Neutral | 0.39 | 0.05 | 0.08 | Sadness | 0.30 | 0.45 | 0.36 | Surprise | 0.00 | 0.00 | 0.00 |
| Accuracy | | | 0.21 |
| Macro Average | 0.19 | 0.18 | 0.16 | Weighted Average | 0.29 | 0.21 | 0.21 |
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