Published June 25, 2025
| Version v2
Model
Open
SCOREQ: Speech Quality Assessment with Contrastive Regression - PyTorch weights
Authors/Creators
-
1.
University College Dublin
- 2. Insight Centre for Data Analytics
Description
| Model | Training Set/Domain | Usage Mode | Margin |
| adapt_nr_telephone.pt/.onnx | NISQA TRAIN SIM / Telephone speech | No-reference | Adaptive |
| fixed_nmr_telephone.pt/.onnx | NISQA TRAIN SIM / Telephone speech | Non-matching reference, full-reference | Constant |
| adapt_nr_synthetic.pt/.onnx | VoiceMOS 22 / Synthetic speech | No-reference | Adaptive |
| fixed_nmr_synthetic.pt/.onnx | VoiceMOS 22 / Synthetic speech | Non-matching reference | Constant |
Notes
Cite as
Alessandro Ragano, Jan Skoglund, and Andrew Hines (2024) SCOREQ: Speech Quality Assessment with Contrastive Regression, Advances in Neural Information Processing Systems (NeurIPS) 2024.
Files
Files
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md5:404b659fcf1208e619f7a71831967cfe
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378.0 MB | Download |
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378.4 MB | Download |
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378.0 MB | Download |
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378.4 MB | Download |
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378.4 MB | Download |