2 papers
cs.SD2026
Assessing the Energy and Carbon Emissions of Neural Speaker Verification Model in Training and Inference
Hugo Leguillier, Driss Matrouf, Guillaume Lechien +1
Deep-learning speaker verification (SV) increasingly relies on deep neural network backbones, whose environmental impact remains largely undocumented. In this paper, we conduct an…
cs.SD2026
On Low-Bit Quantization Errors in Speaker Verification: Diagnostic and Mitigation
Hugo Leguillier, Driss Matrouf, Guillaume Lechien +1
Although low-bit quantization provides practical means to deploy speaker verification on resource-constrained devices, its effects on speaker verification performance remain poorly…