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Found 12 papers, 3 papers with code
Machine Translation with Pre-specified Target-side Words Using a Semi-autoregressive Model
We introduce our TMU Japanese-to-English system, which employs a semi-autoregressive model, to tackle the WAT 2021 restricted translation task.
Translation of New Named Entities from English to Chinese
New things are being created and new words are constantly being added to languages worldwide.
TMU Japanese-English Multimodal Machine Translation System for WAT 2020
Subsequently, we pretrain a translation model on the augmented noisy data, and then fine-tune it on the clean data.
Korean-to-Japanese Neural Machine Translation System using Hanja Information
In this paper, we describe our TMU neural machine translation (NMT) system submitted for the Patent task (Korean→Japanese) of the 7th Workshop on Asian Translation (WAT 2020, Nakazawa et al., 2020).
Construction of a Quality Estimation Dataset for Automatic Evaluation of Japanese Grammatical Error Correction
Therefore, in this study, we created a quality estimation dataset with manual evaluation to build an automatic evaluation model for Japanese GEC.
Zero-shot North Korean to English Neural Machine Translation by Character Tokenization and Phoneme Decomposition
The primary limitation of North Korean to English translation is the lack of a parallel corpus; therefore, high translation accuracy cannot be achieved.
English-to-Japanese Diverse Translation by Combining Forward and Backward Outputs
We introduce our TMU system that is submitted to The 4th Workshop on Neural Generation and Translation (WNGT2020) to English-to-Japanese (En→Ja) track on Simultaneous Translation And Paraphrase for Language Education (STAPLE) shared task.
Keyframe Segmentation and Positional Encoding for Video-guided Machine Translation Challenge 2020
Video-guided machine translation as one of multimodal neural machine translation tasks targeting on generating high-quality text translation by tangibly engaging both video and text.
Towards Multimodal Simultaneous Neural Machine Translation
Simultaneous translation involves translating a sentence before the speaker's utterance is completed in order to realize real-time understanding in multiple languages.
Debiasing Word Embeddings Improves Multimodal Machine Translation
In this study, we examine various kinds of word embeddings and introduce two debiasing techniques for three multimodal NMT models and two language pairs -- English-German translation and English-French translation.
Multimodal Machine Translation with Embedding Prediction
Multimodal machine translation is an attractive application of neural machine translation (NMT).
