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Low-bit quantization errors impact speaker verification systems

Researchers have investigated the impact of low-bit quantization on speaker verification systems, finding that performance degradation is not solely due to weight distortion. They identified a critical point at 2-bit quantization where score errors and decision flips become significant, particularly near the floating-point threshold. To address this, a calibrated multi-precision cascade approach was proposed, which uses 2-bit quantization for most trials while escalating ambiguous cases, thereby maintaining near FP32 performance with reduced computational and memory costs. AI

RANK_REASON This is a research paper detailing findings and proposing a new method for low-bit quantization in speaker verification. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Mickael Rouvier ·

    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 Re…