Andy Way
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View article: Findings of the WMT 2024 Shared Task on Discourse-Level Literary Translation
Findings of the WMT 2024 Shared Task on Discourse-Level Literary Translation Open
Following last year, we have continued to host the WMT translation shared task this year, the second edition of the Discourse-Level Literary Translation. We focus on three language directions: Chinese-English, Chinese-German, and Chinese-R…
View article: Leveraging LLMs for MT in Crisis Scenarios: a blueprint for low-resource languages
Leveraging LLMs for MT in Crisis Scenarios: a blueprint for low-resource languages Open
In an evolving landscape of crisis communication, the need for robust and adaptable Machine Translation (MT) systems is more pressing than ever, particularly for low-resource languages. This study presents a comprehensive exploration of le…
View article: How Much Data is Enough Data? Fine-Tuning Large Language Models for In-House Translation: Performance Evaluation Across Multiple Dataset Sizes
How Much Data is Enough Data? Fine-Tuning Large Language Models for In-House Translation: Performance Evaluation Across Multiple Dataset Sizes Open
Decoder-only LLMs have shown impressive performance in MT due to their ability to learn from extensive datasets and generate high-quality translations. However, LLMs often struggle with the nuances and style required for organisation-speci…
View article: Automating Translation
Automating Translation Open
While the previous chapters have shown how machine translation (MT) can be useful, in this chapter we discuss some of the side-effects and risks that are associated, and how they might be mitigated. With the move to neural MT and approache…
View article: gaHealth: An English-Irish Bilingual Corpus of Health Data
gaHealth: An English-Irish Bilingual Corpus of Health Data Open
Machine Translation is a mature technology for many high-resource language pairs. However in the context of low-resource languages, there is a paucity of parallel data datasets available for developing translation models. Furthermore, the …
View article: Design of an Open-Source Architecture for Neural Machine Translation
Design of an Open-Source Architecture for Neural Machine Translation Open
adaptNMT is an open-source application that offers a streamlined approach to the development and deployment of Recurrent Neural Networks and Transformer models. This application is built upon the widely-adopted OpenNMT ecosystem, and is pa…
View article: Transformers for Low-Resource Languages: Is Féidir Linn!
Transformers for Low-Resource Languages: Is Féidir Linn! Open
The Transformer model is the state-of-the-art in Machine Translation. However, in general, neural translation models often under perform on language pairs with insufficient training data. As a consequence, relatively few experiments have b…
View article: Machine Translation in the Covid domain: an English-Irish case study for\n LoResMT 2021
Machine Translation in the Covid domain: an English-Irish case study for\n LoResMT 2021 Open
Translation models for the specific domain of translating Covid data from\nEnglish to Irish were developed for the LoResMT 2021 shared task. Domain\nadaptation techniques, using a Covid-adapted generic 55k corpus from the\nDirectorate Gene…
View article: Machine Translation in the Covid domain: an English-Irish case study for LoResMT 2021
Machine Translation in the Covid domain: an English-Irish case study for LoResMT 2021 Open
Translation models for the specific domain of translating Covid data from English to Irish were developed for the LoResMT 2021 shared task. Domain adaptation techniques, using a Covid-adapted generic 55k corpus from the Directorate General…
View article: Why Literary Translators should embrace Translation Technology
Why Literary Translators should embrace Translation Technology Open
Machine translation (MT) quality has improved significantly with the advent of neural techniques. Some communications about these improvements have been the product of overeager marketing hype, but MT is playing a real role in the lives of…
View article: Fine-tuning Large Language Models for Adaptive Machine Translation
Fine-tuning Large Language Models for Adaptive Machine Translation Open
This paper presents the outcomes of fine-tuning Mistral 7B, a general-purpose large language model (LLM), for adaptive machine translation (MT). The fine-tuning process involves utilising a combination of zero-shot and one-shot translation…
View article: adaptMLLM: Fine-Tuning Multilingual Language Models on Low-Resource Languages with Integrated LLM Playgrounds
adaptMLLM: Fine-Tuning Multilingual Language Models on Low-Resource Languages with Integrated LLM Playgrounds Open
The advent of Multilingual Language Models (MLLMs) and Large Language Models (LLMs) has spawned innovation in many areas of natural language processing. Despite the exciting potential of this technology, its impact on developing high-quali…
View article: SentAlign: Accurate and Scalable Sentence Alignment
SentAlign: Accurate and Scalable Sentence Alignment Open
We present SentAlign, an accurate sentence alignment tool designed to handle very large parallel document pairs. Given user-defined parameters, the alignment algorithm evaluates all possible alignment paths in fairly large documents of tho…
View article: Findings of the WMT 2023 Shared Task on Discourse-Level Literary Translation: A Fresh Orb in the Cosmos of LLMs
Findings of the WMT 2023 Shared Task on Discourse-Level Literary Translation: A Fresh Orb in the Cosmos of LLMs Open
Translating literary works has perennially stood as an elusive dream in machine translation (MT), a journey steeped in intricate challenges. To foster progress in this domain, we hold a new shared task at WMT 2023, the first edition of the…
View article: Domain Terminology Integration into Machine Translation: Leveraging Large Language Models
Domain Terminology Integration into Machine Translation: Leveraging Large Language Models Open
This paper discusses the methods that we used for our submissions to the WMT 2023 Terminology Shared Task for German-to-English (DE-EN), English-to-Czech (EN-CS), and Chinese-to-English (ZH-EN) language pairs. The task aims to advance mach…
View article: adaptNMT: an open-source, language-agnostic development environment for neural machine translation
adaptNMT: an open-source, language-agnostic development environment for neural machine translation Open
adaptNMT streamlines all processes involved in the development and deployment of RNN and Transformer neural translation models. As an open-source application, it is designed for both technical and non-technical users who work in the field …
View article: Proceedings of the Second International Workshop on Automatic Translation for Signed and Spoken Languages
Proceedings of the Second International Workshop on Automatic Translation for Signed and Spoken Languages Open
\n Contains fulltext :\n 297465.pdf (Publisher’s version ) (Open Access)\n
View article: Building Neural Machine Translation Systems for Multilingual Participatory Spaces
Building Neural Machine Translation Systems for Multilingual Participatory Spaces Open
This work presents the development of the translation component in a multistage, multilevel, multimode, multilingual and dynamic deliberative (M4D2) system, built to facilitate automated moderation and translation in the languages of five …
View article: Adaptive Machine Translation with Large Language Models
Adaptive Machine Translation with Large Language Models Open
Consistency is a key requirement of high-quality translation. It is especially important to adhere to pre-approved terminology and adapt to corrected translations in domain-specific projects. Machine translation (MT) has achieved significa…
View article: Findings of the WMT 2023 Shared Task on Discourse-Level Literary Translation: A Fresh Orb in the Cosmos of LLMs
Findings of the WMT 2023 Shared Task on Discourse-Level Literary Translation: A Fresh Orb in the Cosmos of LLMs Open
Longyue Wang, Zhaopeng Tu, Yan Gu, Siyou Liu, Dian Yu, Qingsong Ma, Chenyang Lyu, Liting Zhou, Chao-Hong Liu, Yufeng Ma, Weiyu Chen, Yvette Graham, Bonnie Webber, Philipp Koehn, Andy Way, Yulin Yuan, Shuming Shi. Proceedings of the Eighth …
View article: Domain Terminology Integration into Machine Translation: Leveraging Large Language Models
Domain Terminology Integration into Machine Translation: Leveraging Large Language Models Open
This paper discusses the methods that we used for our submissions to the WMT 2023 Terminology Shared Task for German-to-English (DE-EN), English-to-Czech (EN-CS), and Chinese-to-English (ZH-EN) language pairs. The task aims to advance mach…
View article: SentAlign: Accurate and Scalable Sentence Alignment
SentAlign: Accurate and Scalable Sentence Alignment Open
We present SentAlign, an accurate sentence alignment tool designed to handle very large parallel document pairs. Given user-defined parameters, the alignment algorithm evaluates all possible alignment paths in fairly large documents of tho…
View article: European Language Equality: Introduction
European Language Equality: Introduction Open
This chapter provides an introduction to the EU-funded project European Language Equality (ELE). It motivates the project by taking a general look at multilingualism, especially with regard to the political equality of all languages in Eur…
View article: European Language Equality
European Language Equality Open
This open access book presents a comprehensive collection of the European Language Equality (ELE) project’s results, its strategic agenda and roadmap with key recommendations to the European Union on how to achieve digital language equalit…