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pro vyhledávání: '"Carmo, Félix do"'
This paper investigates whether large language models (LLMs) are state-of-the-art quality estimators for machine translation of user-generated content (UGC) that contains emotional expressions, without the use of reference translations. To achieve th
Externí odkaz:
http://arxiv.org/abs/2410.06338
Autor:
Carmo, Félix do, Kanojia, Diptesh
The tutorial describes the concept of edit distances applied to research and commercial contexts. We use Translation Edit Rate (TER), Levenshtein, Damerau-Levenshtein, Longest Common Subsequence and $n$-gram distances to demonstrate the frailty of st
Externí odkaz:
http://arxiv.org/abs/2410.05881
Machine translation (MT) of user-generated content (UGC) poses unique challenges, including handling slang, emotion, and literary devices like irony and sarcasm. Evaluating the quality of these translations is challenging as current metrics do not fo
Externí odkaz:
http://arxiv.org/abs/2410.03277
In this paper, we focus on how current Machine Translation (MT) tools perform on the translation of emotion-loaded texts by evaluating outputs from Google Translate according to a framework proposed in this paper. We propose this evaluation framework
Externí odkaz:
http://arxiv.org/abs/2306.11900
Publikováno v:
Linguistik International 2020
Although emotions are universal concepts, transferring the different shades of emotion from one language to another may not always be straightforward for human translators, let alone for machine translation systems. Moreover, the cognitive states are
Externí odkaz:
http://arxiv.org/abs/2106.10719
Publikováno v:
Translation Spaces; 2024, Vol. 13 Issue 1, p54-77, 24p
Autor:
Shterionov, Dimitar, Carmo, Félix do, Moorkens, Joss, Hossari, Murhaf, Wagner, Joachim, Paquin, Eric, Schmidtke, Dag, Groves, Declan, Way, Andy
Publikováno v:
Machine Translation; Sep2020, Vol. 34 Issue 2/3, p67-96, 30p