Papers by Massa Baali
SVeritas: Benchmark for Robust Speaker Verification under Diverse Conditions (2025.findings-emnlp)
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| Challenge: | Existing benchmarks only evaluate a subset of potential conditions, missing others entirely. |
| Approach: | a new benchmark suite evaluates speaker verification models under a variety of stressors . a san francisco-based team evaluates models under natural and background conditions . |
| Outcome: | a new benchmark suite evaluates speaker verification models under stressors under a variety of conditions . the results show that some models perform better under stress conditions than others . |
CAARMA: Class Augmentation with Adversarial Mixup Regularization (2025.findings-emnlp)
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| Challenge: | Speaker verification tasks require inference of unseen classes using specialized losses. |
| Approach: | They propose a class augmentation framework that generates synthetic classes through data mixing in the embedding space. |
| Outcome: | The proposed framework improves speaker verification tasks by 8% over baseline models. |