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20172026
most citedAn Empirical Comparison of Simple Domain Adaptation Methods for Neural Machine Translation

51 citations · 147 across the 23 of their papers we have counts for

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Showing 2023Show all

7 papers · 1 filter

cs.CL2023

Bilingual Corpus Mining and Multistage Fine-Tuning for Improving Machine Translation of Lecture Transcripts

Haiyue Song, Raj Dabre, Chenhui Chu +2

Lecture transcript translation helps learners understand online courses, however, building a high-quality lecture machine translation system lacks publicly available parallel corpo…

cs.CL2023

Video-Helpful Multimodal Machine Translation

Yihang Li, Shuichiro Shimizu, Chenhui Chu +2

Existing multimodal machine translation (MMT) datasets consist of images and video captions or instructional video subtitles, which rarely contain linguistic ambiguity, making visu…

cs.CL2023

Reasoning before Responding: Integrating Commonsense-based Causality Explanation for Empathetic Response Generation

Yahui Fu, Koji Inoue, Chenhui Chu +1

Recent approaches to empathetic response generation try to incorporate commonsense knowledge or reasoning about the causes of emotions to better understand the user's experiences a…

cs.CL20235 cited

SelfSeg: A Self-supervised Sub-word Segmentation Method for Neural Machine Translation

Haiyue Song, Raj Dabre, Chenhui Chu +2

Sub-word segmentation is an essential pre-processing step for Neural Machine Translation (NMT). Existing work has shown that neural sub-word segmenters are better than Byte-Pair En…

cs.CL2023

Towards Speech Dialogue Translation Mediating Speakers of Different Languages

Shuichiro Shimizu, Chenhui Chu, Sheng Li +1

We present a new task, speech dialogue translation mediating speakers of different languages. We construct the SpeechBSD dataset for the task and conduct baseline experiments. Furt…

cs.CL2023

Variable-length Neural Interlingua Representations for Zero-shot Neural Machine Translation

Zhuoyuan Mao, Haiyue Song, Raj Dabre +2

The language-independency of encoded representations within multilingual neural machine translation (MNMT) models is crucial for their generalization ability on zero-shot translati…