WebDecision rules play an important role in the tuning and decoding steps of statistical machine translation. The traditional decision rule selects the candidate WebAbstract. This paper presents a machine learning approach to the study of translationese. The goal is to train a computer system to distinguish between translated and non-translated text, in order to determine the characteristic features that influence the classifiers. Several algorithms reach up to 97.62% success rate on a technical dataset.
The Features of Translationese - Between Human and Machine
Web1 de abr. de 2015 · Translated texts, in any language, can be considered a dialect of that language, known as ‘translationese’. Several characteristics of translationese have … Web11 de dez. de 2015 · A new approach to the study of translationese: Machine-learning the difference between original and translated text. Literary and Linguistic Computing 21(3), 259–274 (2006) CrossRef Google Scholar Ilisei, I., Inkpen, D., Corpas Pastor, G., Mitkov, R.: Identification of translationese: a machine learning approach. trying to get used to it
Statistical Power and Translationese in Machine Translation …
Web3 de abr. de 2024 · Information density and quality estimation features as translationese indicators for human translation classification. In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, San Diego, CA, pp. 960–970. http://yuedu.woyoujk.com/k/78602.html Web3 de abr. de 2024 · Information density and quality estimation features as translationese indicators for human translation classification. In Proceedings of the 2016 Conference of … trying to get to you lyrics and chords