Translation Deserves Better: Analyzing Translation Artifacts in Cross-lingual Visual Question Answering

no code implementations • 4 Jun 2024 • ChaeHun Park, Koanho Lee, Hyesu Lim, Jaeseok Kim, Junmo Park, Yu-Jung Heo, Du-Seong Chang, Jaegul Choo

Building a reliable visual question answering~(VQA) system across different languages is a challenging problem, primarily due to the lack of abundant samples for training.

Data Augmentation Machine Translation +3

Attention based on-device streaming speech recognition with large speech corpus

no code implementations • 2 Jan 2020 • Kwangyoun Kim, Kyungmin Lee, Dhananjaya Gowda, Junmo Park, Sungsoo Kim, Sichen Jin, Young-Yoon Lee, Jinsu Yeo, Daehyun Kim, Seokyeong Jung, Jungin Lee, Myoungji Han, Chanwoo Kim

In this paper, we present a new on-device automatic speech recognition (ASR) system based on monotonic chunk-wise attention (MoChA) models trained with large (> 10K hours) corpus.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3