24 citations · 73 across the 19 of their papers we have counts for
4 papers · 1 filter
An Empirical Study of Contextual Data Augmentation for Japanese Zero Anaphora Resolution
Ryuto Konno, Yuichiroh Matsubayashi, Shun Kiyono +3
One critical issue of zero anaphora resolution (ZAR) is the scarcity of labeled data. This study explores how effectively this problem can be alleviated by data augmentation. We ad…
A Self-Refinement Strategy for Noise Reduction in Grammatical Error Correction
Masato Mita, Shun Kiyono, Masahiro Kaneko +2
Existing approaches for grammatical error correction (GEC) largely rely on supervised learning with manually created GEC datasets. However, there has been little focus on verifying…
Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction
Masahiro Kaneko, Masato Mita, Shun Kiyono +2
This paper investigates how to effectively incorporate a pre-trained masked language model (MLM), such as BERT, into an encoder-decoder (EncDec) model for grammatical error correct…
ESPnet-ST: All-in-One Speech Translation Toolkit
Hirofumi Inaguma, Shun Kiyono, Kevin Duh +4
We present ESPnet-ST, which is designed for the quick development of speech-to-speech translation systems in a single framework. ESPnet-ST is a new project inside end-to-end speech…