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Multilingual corpus construction and domain adaptation for low-resource machine translation

低资源机器翻译的多语言语料库构建和领域适应

基本信息

批准号：
22KJ1724
负责人：
宋海越
金额：
$ 1.41万
依托单位：
Kyoto University
依托单位国家：
日本
项目类别：
Grant-in-Aid for JSPS Fellows
财政年份：
2023
资助国家：
日本
起止时间：
2023-03-08 至 2024-03-31
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-22KJ1724/
关键词：
machine translation ChatGPT subword segmentation Machine translation Parallel corpus creation Pre-training Data selection

项目摘要

During this year, I have published 5 papers and one journal paper is under review. For the 3 papers as the first author: 1) the first work published in an international conference AACL-IJCNLP2022 exploits BERT-based unsupervised subword segmentation for neural machine translation which is effective on low-resource to high-resource scenarios; 2) the second work published in a domestic conference NLP2023 utilizes machine translation of prompts for adjusting GPT-3 to Japanese tasks; 3) the third work submitting to the NLP journal leverages information from multiple subword segmenters in a proposed subword-relation-aware attention-mechanism and aligning loss objective. Other works include video-information for multimodal NMT which is published in the JIP journal, exploring contrastive word alignments for multilingual NMT which is published in a top international conference NAACL2022, and contrastive pre-training for relation extraction which is published in a top international conference EMNLP2022. Two co-authored papers are under review for international conference ACL2023 and one for EAMT2023. I have also participated in symposiums on campus and workshops in Japan, and communicate with many researchers there.Moreover, I took an internship at NICT in a national lab focusing on machine translation, and we have applied one patent for the BERT-based unsupervised subword segmentation.

在这一年里，我发表了5篇论文，一篇期刊论文正在审查中。对于作为第一作者的3篇论文：1）在国际会议AACL-IJCNLP 2022上发表的第一篇工作利用基于BERT的无监督子分词进行神经机器翻译，该方法在低资源到高资源场景下有效; 2）在国内会议NLP 2023上发表的第二篇工作利用机器翻译提示将GPT-3调整为日语任务; 3）提交给NLP期刊的第三个作品在所提出的子词关系感知注意力机制和对齐损失目标中利用来自多个子词分段器的信息。其他作品包括发表在JIP杂志上的多模态NMT的视频信息，在顶级国际会议NAACL 2022上发表的多语言NMT的对比词对齐探索，以及在顶级国际会议EMNLP 2022上发表的关系提取的对比预训练。两篇合著的论文正在为国际会议ACL 2023和EAMT 2023进行审查。我还参加了日本的校园研讨会和工作坊，并与那里的许多研究人员进行了交流。此外，我还在NICT的一个专注于机器翻译的国家实验室实习，我们已经申请了一项基于BERT的无监督子分词专利。