paper-with-me

홈 › Papers

Assessing the Comprehensibility of Automatic Translations (ArisToCAT)

2020-11-01 · EAMT 2020 11 · Lieve Macken, Margot Fonteyne, Arda Tezcan, Joke Daems

The ArisToCAT project aims to assess the comprehensibility of ‘raw’ (unedited) MT output for readers who can only rely on the MT output. In this project description, we summarize the main results of the project and present future work.

📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Relations between comprehensibility and adequacy errors in machine translation output

2020-11-01 · CONLL 2020 · Maja Popovi{\'c}

This work presents a detailed analysis of translation errors perceived by readers as comprehensibility and/or adequacy issues. The main finding is that good comprehensibility, similarly to good fluency, can mask a number…

Machine TranslationTranslationWord Translation

Toward Determining the Comprehensibility of Machine Translations

2012-06-01 · WS 2012 6 · Tucker Maney, Linda Sibert, Dennis Perzanowski, Kalyan Gupta 외
Machine Translation

Flagging Comprehensibility Issues in Hindi Text with Question Answering

2021-11-16 · ACL ARR November 2021 11 · Anonymous

There is a critical need for checking the quality of translations while localizing important content across all the industries. This paper presents question-answering based techniques to check the comprehensibility of a …

Question AnsweringTranslation

PET: a Tool for Post-editing and Assessing Machine Translation

2012-05-01 · LREC 2012 5 · Wilker Aziz, Sheila Castilho, Lucia Specia

Given the significant improvements in Machine Translation (MT) quality and the increasing demand for translations, post-editing of automatic translations is becoming a popular practice in the translation industry. It has…

Machine TranslationSentenceTranslation

Google Translate Error Analysis for Mental Healthcare Information: Evaluating Accuracy, Comprehensibility, and Implications for Multilingual Healthcare Communication

2024-02-06 · Jaleh Delfani, Constantin Orasan, Hadeel Saadany, Ozlem Temizoz 외

This study explores the use of Google Translate (GT) for translating mental healthcare (MHealth) information and evaluates its accuracy, comprehensibility, and implications for multilingual healthcare communication throu…

Translation