Intent Classification On Slurp
Metriken
Accuracy (%)
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | Accuracy (%) | Paper Title | Repository |
|---|---|---|---|
| TDT 0-8 | 90.07 | Efficient Sequence Transduction by Jointly Predicting Tokens and Durations | - |
| Multi-SLURP | 78.33 | SLURP: A Spoken Language Understanding Resource Package | - |
| Finstreder (Quartznet) | 43.15 | Finstreder: Simple and fast Spoken Language Understanding with Finite State Transducers using modern Speech-to-Text models | - |
| Finstreder (Conformer) | 53.11 | Finstreder: Simple and fast Spoken Language Understanding with Finite State Transducers using modern Speech-to-Text models | - |
| Partially Fine-tuned HuBERT | 87.51 | A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding | - |
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