BRAPT: A New Metric for Translation Evaluation Based on Psycholinguistic Perspectives
| Autor: | Rafael Guimarães Rodrigues, Kaio Tavares Rodrigues, Rodrigo Reis Gomes, Gustavo Paiva Guedes, Eduardo Ogasawara, Lilian Ferrari |
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| Rok vydání: | 2020 |
| Předmět: |
General Computer Science
Point (typography) business.industry Computer science 020208 electrical & electronic engineering 020206 networking & telecommunications 02 engineering and technology computer.software_genre Semantics Translation (geometry) language.human_language Proof of concept Similarity (psychology) Metric (mathematics) ComputingMethodologies_DOCUMENTANDTEXTPROCESSING 0202 electrical engineering electronic engineering information engineering language NIST Artificial intelligence Electrical and Electronic Engineering Portuguese business computer Natural language processing |
| Zdroj: | IEEE Latin America Transactions. 18:1264-1271 |
| ISSN: | 1548-0992 |
| DOI: | 10.1109/tla.2020.9099768 |
| Popis: | There are some metrics to evaluate automatic text translations in the literature. However, the state-of-the-art of these metrics still has limitations. One of them is the dependence of an exact and ordered pairing of words for evaluating similarity among texts. Another, is the non-consideration of the semantics of the text in such comparison. Previous studies point out the need to analyze the semantics of words in the evaluation of translations. In this scenario, this paper presents a novel metric capable of evaluating the differences in automatic text translations that takes into account the semantics of the words presented in the texts. As a proof of concept, we selected ten journalistic texts written in English. These texts have been translated to Portuguese by specialists and by automatic text translation tools. Experimental results show the potential of the proposed metric in evaluating these translations, indicating it can perform better than the state-of-the-art metric. |
| Databáze: | OpenAIRE |
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