Samsung and University of Edinburgh’s System for the IWSLT 2019
This paper describes the joint submission to the IWSLT 2019 English to Czech task by Samsung RD Institute, Poland, and the University of Edinburgh. Our submission was ultimately produced by combining four Transformer systems through a mixture of ensembling and reranking.
Code (0)
등록된 구현이 없습니다.
Tasks
RerankingSimilar Papers 제목 키워드 기반
The Samsung and University of Edinburgh’s submission to IWSLT17
This paper describes the joint submission of Samsung Research and Development, Warsaw, Poland and the University of Edinburgh team to the IWSLT MT task for TED talks. We took part in two translation directions, en-de and…
Decoderde-enDomain AdaptationTranslationSamsung and University of Edinburgh’s System for the IWSLT 2018 Low Resource MT Task
This paper describes the joint submission to the IWSLT 2018 Low Resource MT task by Samsung R&D Institute, Poland, and the University of Edinburgh. We focused on supplementing the very limited in-domain Basque-English tr…
The University of Edinburgh’s systems submission to the MT task at IWSLT
This paper describes the submission of the University of Edinburgh team to the IWSLT MT task for TED talks. We took part in four translation directions, en-de, de-en, en-fr, and fr-en. The models have been trained with a…
Decoderde-enDomain Adaptationfr-en+1Character Mapping and Ad-hoc Adaptation: Edinburgh's IWSLT 2020 Open Domain Translation System
This paper describes the University of Edinburgh{'}s neural machine translation systems submitted to the IWSLT 2020 open domain Japanese$\leftrightarrow$Chinese translation task. On top of commonplace techniques like tok…
Machine TranslationTranslationThe University of Edinburgh’s Submission to the IWSLT21 Simultaneous Translation Task
We describe our submission to the IWSLT 2021 shared task on simultaneous text-to-text English-German translation. Our system is based on the re-translation approach where the agent re-translates the whole source prefix e…
Language ModelingLanguage ModellingMachine TranslationNMT+2