Spoken Language Understanding On Snips 1
Metrics
Accuracy-EN (%)
Accuracy-FR (%)
Results
Performance results of various models on this benchmark
Model Name | Accuracy-EN (%) | Accuracy-FR (%) | Paper Title | Repository |
|---|---|---|---|---|
| 47.8 | 42.3 | Spoken Language Understanding on the Edge | ||
| Finstreder (Quartznet) | 77.6 | 77.8 | Finstreder: Simple and fast Spoken Language Understanding with Finite State Transducers using modern Speech-to-Text models | |
| Snips | 68.7 | 75.1 | Spoken Language Understanding on the Edge | |
| Finstreder (Conformer, character-based) | 87.9 | 86.5 | Finstreder: Simple and fast Spoken Language Understanding with Finite State Transducers using modern Speech-to-Text models | |
| Finstreder (Conformer) | 80.4 | 78.3 | Finstreder: Simple and fast Spoken Language Understanding with Finite State Transducers using modern Speech-to-Text models |
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