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Comparison of TinyML-based voice assistant models.
| Model | Dataset | Accuracy (%) | Latency (ms) | Energy consumption |
|---|---|---|---|---|
| Transformer-based model | Common voice dataset (Multilingual) | 92.0 | 80–150 | High |
| Hybrid CNN-RNN | CHiME Speech Dataset (Noisy Environments) | 89.5 | 100–250 | Moderate |
| DNN | Gesture Dataset | 99.0 | 50–100 | High |
| CNN | UrbanSound8K | 94.0 | 30–70 | Moderate |
| RNN | AudioSet | 95.0 | 100–200 | High |
| Decision Tree | ESC-50 | 90.0 | 10–30 | Low |
| SVM | VoxForge dataset (Multilingual Speech) | 91.5 | 90–180 | Moderate |
