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eess.AS2025
StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models
Yeona Hong, Hyewon Han, Woo-jin Chung +1
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…
eess.AS2024★ 1 cited
Optimization of DNN-based speaker verification model through efficient quantization technique
Yeona Hong, Woo-Jin Chung, Hong-Goo Kang
As Deep Neural Networks (DNNs) rapidly advance in various fields, including speech verification, they typically involve high computational costs and substantial memory consumption,…
eess.AS2020
Adaptable Multi-Domain Language Model for Transformer ASR
Taewoo Lee, Min-Joong Lee, Tae Gyoon Kang +10
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 ca…