1 citations · 1 across the 7 of their papers we have counts for
7 papers
MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition
Sangmin Lee, Woojin Chung, Woongjib Choi +1
Massively multilingual automatic speech recognition (ASR) models covering hundreds of languages must maintain robust performance across diverse linguistic and acoustic conditions.…
UniCoM: A Universal Code-Switching Speech Generator
Sangmin Lee, Woojin Chung, Seyun Um +1
Code-switching (CS), the alternation between two or more languages within a single speaker's utterances, is common in real-world conversations and poses significant challenges for…
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…
LAMA-UT: Language Agnostic Multilingual ASR through Orthography Unification and Language-Specific Transliteration
Sangmin Lee, Woo-Jin Chung, Hong-Goo Kang
Building a universal multilingual automatic speech recognition (ASR) model that performs equitably across languages has long been a challenge due to its inherent difficulties. To a…
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,…
Speaker-Independent Acoustic-to-Articulatory Inversion through Multi-Channel Attention Discriminator
Woo-Jin Chung, Hong-Goo Kang
We present a novel speaker-independent acoustic-to-articulatory inversion (AAI) model, overcoming the limitations observed in conventional AAI models that rely on acoustic features…
C2C: Cough to COVID-19 Detection in BHI 2023 Data Challenge
Woo-Jin Chung, Miseul Kim, Hong-Goo Kang
This report describes our submission to BHI 2023 Data Competition: Sensor challenge. Our Audio Alchemists team designed an acoustic-based COVID-19 diagnosis system, Cough to COVID-…