1 code implementation • 3 Jun 2023 • Changhun Kim, Joonhyung Park, Hajin Shim, Eunho Yang
Automatic speech recognition (ASR) models are frequently exposed to data distribution shifts in many real-world scenarios, leading to erroneous predictions.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • CVPR 2023 • Gyeongman Kim, Hajin Shim, Hyunsu Kim, Yunjey Choi, Junho Kim, Eunho Yang
Inspired by the impressive performance of recent face image editing methods, several studies have been naturally proposed to extend these methods to the face video editing task.
no code implementations • 2 Dec 2021 • Yeonsung Jung, Hajin Shim, June Yong Yang, Eunho Yang
Deep neural networks (DNNs), despite their impressive ability to generalize over-capacity networks, often rely heavily on malignant bias as shortcuts instead of task-related information for discriminative tasks.
no code implementations • 10 Nov 2021 • Joonhyung Park, Hajin Shim, Eunho Yang
Graph-structured datasets usually have irregular graph sizes and connectivities, rendering the use of recent data augmentation techniques, such as Mixup, difficult.
no code implementations • 26 Mar 2021 • Jaeyun Song, Hajin Shim, Eunho Yang
Despite the feature of real-time decoding, Monotonic Multihead Attention (MMA) shows comparable performance to the state-of-the-art offline methods in machine translation and automatic speech recognition (ASR) tasks.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • NeurIPS 2018 • Hajin Shim, Sung Ju Hwang, Eunho Yang
We consider the problem of active feature acquisition where the goal is to sequentially select the subset of features in order to achieve the maximum prediction performance in the most cost-effective way at test time.
no code implementations • 18 Sep 2017 • Hajin Shim, Sung Ju Hwang, Eunho Yang
We consider the problem of active feature acquisition, where we sequentially select the subset of features in order to achieve the maximum prediction performance in the most cost-effective way.