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🦜 Synthetic Voice Detection • 15 items • Updated • 2
How to use MattyB95/AST-ASVspoof5-Synthetic-Voice-Detection with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="MattyB95/AST-ASVspoof5-Synthetic-Voice-Detection") # Load model directly
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification
extractor = AutoFeatureExtractor.from_pretrained("MattyB95/AST-ASVspoof5-Synthetic-Voice-Detection")
model = AutoModelForAudioClassification.from_pretrained("MattyB95/AST-ASVspoof5-Synthetic-Voice-Detection")This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the audiofolder dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0042 | 1.0 | 22795 | 1.6954 | 0.8470 | 0.8942 | 0.9672 | 0.8314 |
| 0.0 | 2.0 | 45590 | 1.5632 | 0.8489 | 0.9014 | 0.9157 | 0.8875 |
| 0.0 | 3.0 | 68385 | 2.2821 | 0.8333 | 0.8892 | 0.9209 | 0.8595 |
Base model
MIT/ast-finetuned-audioset-10-10-0.4593