title: GenPTQ: Green Post-Training Quantization for Large-Scale ASR Models with Mixed-Precision Bit Allocation
abstract: Large-scale models have achieved state-of-theart performance in automatic speech recognition (ASR), but their high memory and computation demands pose significant challenges for deployment.To address these challenges, weight-only quantization is widely adopted in large-scale models, where weights dominate memory usage, as it enables efficient compression with minimal accuracy degradation compared to activation quantization.Accordingly, most prior quantization studies for ASR models have focused 