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Yeona Hong

2 accepted papers

2025

StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models

ICASSP 2025accepted

In this paper, we propose StableQuant, a novel adaptive post-training quantization (PTQ) algorithm for widely used speech foundation models (SFMs). While PTQ has been successfully employed for compressing large language models (LLMs) due to its ability to bypass additional fine-tuning, directly appl…

Cited by 0SourceScholar
2021

Adaptable Multi-Domain Language Model for Transformer ASR

ICASSP 2021accepted

We propose an adapter based multi-domain Transformer based language model (LM) for Transformer ASR. The model consists of a big size common LM and small size adapters. The model can perform multi-domain adaptation with only the small size adapters and its related layers. The proposed model can reuse…

Cited by 0SourceScholar