Machine vs Human Translation of Formal Neologisms in Literature
This article compares the output of three neural machine translation systems (Google Translate, DeepL, and Phrase TMS) and human translation (undergraduate level students, English into Spanish). It focuses on five formal neologisms extracted from literary texts, thus considering creativity, and tech...
| Authors: | , |
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| Format: | article |
| Publication Date: | 2023 |
| Country: | España |
| Institution: | Universitat Autònoma de Barcelona |
| Repository: | Dipòsit Digital de Documents de la UAB |
| Language: | English |
| OAI Identifier: | oai:ddd.uab.cat:286793 |
| Online Access: | https://ddd.uab.cat/record/286793 https://dx.doi.org/urn:doi:10.5565/rev/tradumatica.338 |
| Access Level: | Open access |
| Keyword: | Traducción automática Neologismos formales Traducción literaria Traducción humana Herramientas tecnológicas Recursos tecnológicos Creatividad Traducció automàtica Neologismes formals Traducció literària Eines tecnològiques Recursos tecnològics Creativitat Machine translation Formal neologisms Literary translation Human translation Technological tools Technological resources Creativity |
| Summary: | This article compares the output of three neural machine translation systems (Google Translate, DeepL, and Phrase TMS) and human translation (undergraduate level students, English into Spanish). It focuses on five formal neologisms extracted from literary texts, thus considering creativity, and technology adoption and training. |
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