24 citations · 134 across the 37 of their papers we have counts for
10 papers · 1 filter
Dynamic Fusion: Attentional Language Model for Neural Machine Translation
Michiki Kurosawa, Mamoru Komachi
Neural Machine Translation (NMT) can be used to generate fluent output. As such, language models have been investigated for incorporation with NMT. In prior investigations, two mod…
Improving Context-aware Neural Machine Translation with Target-side Context
Hayahide Yamagishi, Mamoru Komachi
In recent years, several studies on neural machine translation (NMT) have attempted to use document-level context by using a multi-encoder and two attention mechanisms to read the…
Machine Translation Evaluation with BERT Regressor
Hiroki Shimanaka, Tomoyuki Kajiwara, Mamoru Komachi
We introduce the metric using BERT (Bidirectional Encoder Representations from Transformers) (Devlin et al., 2019) for automatic machine translation evaluation. The experimental re…
Towards Unsupervised Grammatical Error Correction using Statistical Machine Translation with Synthetic Comparable Corpus
Satoru Katsumata, Mamoru Komachi
We introduce unsupervised techniques based on phrase-based statistical machine translation for grammatical error correction (GEC) trained on a pseudo learner corpus created by Goog…
Debiasing Word Embeddings Improves Multimodal Machine Translation
Tosho Hirasawa, Mamoru Komachi
In recent years, pretrained word embeddings have proved useful for multimodal neural machine translation (NMT) models to address the shortage of available datasets. However, the in…
Multi-Head Multi-Layer Attention to Deep Language Representations for Grammatical Error Detection
Masahiro Kaneko, Mamoru Komachi
It is known that a deep neural network model pre-trained with large-scale data greatly improves the accuracy of various tasks, especially when there are resource constraints. Howev…
Multi-task Learning for Japanese Predicate Argument Structure Analysis
Hikaru Omori, Mamoru Komachi
An event-noun is a noun that has an argument structure similar to a predicate. Recent works, including those considered state-of-the-art, ignore event-nouns or build a single model…
Multimodal Machine Translation with Embedding Prediction
Tosho Hirasawa, Hayahide Yamagishi, Yukio Matsumura +1
Multimodal machine translation is an attractive application of neural machine translation (NMT). It helps computers to deeply understand visual objects and their relations with nat…
Chinese-Japanese Unsupervised Neural Machine Translation Using Sub-character Level Information
Longtu Zhang, Mamoru Komachi
Unsupervised neural machine translation (UNMT) requires only monolingual data of similar language pairs during training and can produce bi-directional translation models with relat…
Divide and Generate: Neural Generation of Complex Sentences
Tomoya Ogata, Mamoru Komachi, Tomoya Takatani
We propose a task to generate a complex sentence from a simple sentence in order to amplify various kinds of responses in the database. We first divide a complex sentence into a ma…