On Low-Bit Quantization Errors in Speaker Verification: Diagnostic and Mitigation
Although low-bit quantization provides practical means to deploy speaker verification on resource-constrained devices, its effects on speaker verification performance remain poorly understood. In this paper, we study uniform K-means quantization-aware training of ResNet-36 and ResNet-200 through joint layer-wise and score-level analyses. Our layer-wise analysis highlights fragile components and shows that score degradation is not fully explained by weight distortion alone. We identify a clear knee point at 2 bits, with larger score drift and harmful decision flips concentrated near the FP32 threshold. Our score-level analysis reveals where and how score errors emerge under extreme quantiz...
| Authors | Hugo Leguillier, Driss Matrouf, Guillaume Lechien et al. |
|---|---|
| Primary category | cs.SD |
| Published | 6 June 2026 |
| Last updated at source | 6 June 2026 |
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