3 papers
cs.CL2021
SSMix: Saliency-Based Span Mixup for Text Classification
Soyoung Yoon, Gyuwan Kim, Kyumin Park
Data augmentation with mixup has shown to be effective on various computer vision tasks. Despite its great success, there has been a hurdle to apply mixup to NLP tasks since text c…
cs.CL2021
KLUE: Korean Language Understanding Evaluation
Sungjoon Park, Jihyung Moon, Sungdong Kim +28
We introduce Korean Language Understanding Evaluation (KLUE) benchmark. KLUE is a collection of 8 Korean natural language understanding (NLU) tasks, including Topic Classification,…
eess.AS2021
STYLER: Style Factor Modeling with Rapidity and Robustness via Speech Decomposition for Expressive and Controllable Neural Text to Speech
Keon Lee, Kyumin Park, Daeyoung Kim
Previous works on neural text-to-speech (TTS) have been addressed on limited speed in training and inference time, robustness for difficult synthesis conditions, expressiveness, an…