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Human Evaluation of Online Machine Translation Services for English/Russian-Croatian / Sanja Seljan ; Marko Tucaković ; Ivan Dunđer.

By: Seljan, Sanja.
Contributor(s): Tucaković, Marko [aut] | Dunđer, Ivan [aut].
Material type: ArticleArticlePublisher: 2015Description: 1089-1098 str.Other title: Human Evaluation of Online Machine Translation Services for English/Russian-Croatian [Naslov na engleskom:].Subject(s): 5.04 | machine translation; human evaluation; Google Translate; Yandex.Translate; English; Russian; Croatian; adequacy; fluency; error analysis; inter-evaluator agreement | machine translation; human evaluation; Google Translate; Yandex.Translate; English; Russian; Croatian; adequacy; fluency; error analysis; inter-evaluator agreementOnline resources: Click here to access online | Click here to access online In: New Contributions in Information Systems and Technologies : vol. 1 World Conference on Information Systems and Technologies, WorldCIST( 2015 ; Eunchal, Madeira) 353 (2015) ; str. 1089-1098Summary: This paper presents results of human evaluation of machine translated texts for one non closely-related language pair, English-Croatian, and for one closely-related language pair, Russian-Croatian. 400 sentences from the domain of tourist guides were analysed, i.e. 100 sentences for each language pair and for two online machine translation services, Google Translate and Yandex.Translate. Human evaluation is made with regard to the criteria of fluency and adequacy. In order to measure internal consistency, Cronbach’s alpha is calculated. Error analysis is made for several categories: untranslated/omitted words, surplus words, morphological errors/wrong word endings, lexical errors/wrong translations, syntactic errors/wrong word order and punctuation errors. At the end of this paper, conclusions and suggestions for further research are given.
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This paper presents results of human evaluation of machine translated texts for one non closely-related language pair, English-Croatian, and for one closely-related language pair, Russian-Croatian. 400 sentences from the domain of tourist guides were analysed, i.e. 100 sentences for each language pair and for two online machine translation services, Google Translate and Yandex.Translate. Human evaluation is made with regard to the criteria of fluency and adequacy. In order to measure internal consistency, Cronbach’s alpha is calculated. Error analysis is made for several categories: untranslated/omitted words, surplus words, morphological errors/wrong word endings, lexical errors/wrong translations, syntactic errors/wrong word order and punctuation errors. At the end of this paper, conclusions and suggestions for further research are given.

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