4 papers
Towards Truly Multilingual ASR: Generalizing Code-Switching ASR to Unseen Language Pairs
Gio Paik, Hyunseo Shin, Soungmin Lee
Automatic Speech Recognition (ASR) has become a key technology for human--AI interaction. However, code-switching ASR (CS-ASR) remains particularly challenging due to the severe sc…
HiKE: Hierarchical Evaluation Framework for Korean-English Code-Switching Speech Recognition
Gio Paik, Yongbeom Kim, Soungmin Lee +2
Despite advances in multilingual automatic speech recognition (ASR), code-switching (CS), the mixing of languages within an utterance common in daily speech, remains a severely und…
MMRefine: Unveiling the Obstacles to Robust Refinement in Multimodal Large Language Models
Gio Paik, Geewook Kim, Jinbae Im
This paper introduces MMRefine, a MultiModal Refinement benchmark designed to evaluate the error refinement capabilities of Multimodal Large Language Models (MLLMs). As the emphasi…
Improving Fine-grained Visual Understanding in VLMs through Text-Only Training
Dasol Choi, Guijin Son, Soo Yong Kim +2
Visual-Language Models (VLMs) have become a powerful tool for bridging the gap between visual and linguistic understanding. However, the conventional learning approaches for VLMs o…