11 citations · 55 across the 19 of their papers we have counts for
29 papers
Learning How to Translate North Korean through South Korean
Hwichan Kim, Sangwhan Moon, Naoaki Okazaki +1
South and North Korea both use the Korean language. However, Korean NLP research has focused on South Korean only, and existing NLP systems of the Korean language, such as neural m…
Construction of a Quality Estimation Dataset for Automatic Evaluation of Japanese Grammatical Error Correction
Daisuke Suzuki, Yujin Takahashi, Ikumi Yamashita +5
In grammatical error correction (GEC), automatic evaluation is an important factor for research and development of GEC systems. Previous studies on automatic evaluation have demons…
Proficiency Matters Quality Estimation in Grammatical Error Correction
Yujin Takahashi, Masahiro Kaneko, Masato Mita +1
This study investigates how supervised quality estimation (QE) models of grammatical error correction (GEC) are affected by the learners' proficiency with the data. QE models for G…
Neural Combinatory Constituency Parsing
Zhousi Chen, Longtu Zhang, Aizhan Imankulova +1
We propose two fast neural combinatory models for constituency parsing: binary and multi-branching. Our models decompose the bottom-up parsing process into 1) classification of tag…
From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding
Rob van der Goot, Ibrahim Sharaf, Aizhan Imankulova +6
The lack of publicly available evaluation data for low-resource languages limits progress in Spoken Language Understanding (SLU). As key tasks like intent classification and slot f…
Sentence Concatenation Approach to Data Augmentation for Neural Machine Translation
Seiichiro Kondo, Kengo Hotate, Masahiro Kaneko +1
Neural machine translation (NMT) has recently gained widespread attention because of its high translation accuracy. However, it shows poor performance in the translation of long se…