Wikipedia can be edited by anyone and thus contains various quality
sent...
During the patient's hospitalization, the physician must record daily
ob...
Automated summarization of clinical texts can reduce the burden of medic...
South and North Korea both use the Korean language. However, Korean NLP
...
In grammatical error correction (GEC), automatic evaluation is an import...
This study investigates how supervised quality estimation (QE) models of...
The lack of publicly available evaluation data for low-resource language...
Neural machine translation (NMT) has recently gained widespread attentio...
Grammatical error correction (GEC) suffers from a lack of sufficient par...
In recent years, pre-trained models have been extensively studied, and
s...
In this paper, we construct a new Japanese speech corpus for speech-base...
Video-guided machine translation as one of multimodal neural machine
tra...
Grammatical error correction (GEC) literature has reported on the
effect...
Simultaneous translation involves translating a sentence before the spea...
Neural Machine Translation (NMT) can be used to generate fluent output. ...
In recent years, several studies on neural machine translation (NMT) hav...
We introduce the metric using BERT (Bidirectional Encoder Representation...
We introduce unsupervised techniques based on phrase-based statistical
m...
In recent years, pretrained word embeddings have proved useful for multi...
In recent years, pretrained word embeddings have proved useful for multi...
It is known that a deep neural network model pre-trained with large-scal...
An event-noun is a noun that has an argument structure similar to a
pred...
Multimodal machine translation is an attractive application of neural ma...
Unsupervised neural machine translation (UNMT) requires only monolingual...
We propose a task to generate a complex sentence from a simple sentence ...
Neural network-based approaches have become widespread for abstractive t...
Recent neural machine translation (NMT) systems have been greatly improv...
Encoder-decoder models typically only employ words that are frequently u...
Neural machine translation (NMT) has a drawback in that can generate onl...
Sentence representations can capture a wide range of information that ca...
This study presents a Long Short-Term Memory (LSTM) neural network appro...
Neural machine translation (NMT) has recently become popular in the fiel...
Previous approaches to training syntax-based sentiment classification mo...
One of the most important problems in machine translation (MT) evaluatio...
An evaluation of distributed word representation is generally conducted ...
Named entity classification is the task of classifying text-based elemen...