Following the Trail of Source Languages in Literary Translations

Autor:	Carl Vogel, Carmen Klaussner, Gerard Lynch
Rok vydání:	2014
Předmět:	Relation (database) Machine translation business.industry Computer science computer.software_genre Linguistics Set (abstract data type) Cross entropy Language transfer Salient Stylometry Artificial intelligence Computational linguistics business computer Natural language processing
Zdroj:	Research and Development in Intelligent Systems XXXI ISBN: 9783319120683 SGAI Conf.
DOI:	10.1007/978-3-319-12069-0_5
Popis:	We build on past research in distinguishing English translations from originally English text, and in guessing the source language where the text is deemed to be a translation. We replicate an extant method in relation to both a reconstruction of the original data set and a fresh data set compiled on an analogous basis. We extend this with an analysis of the features that emerge from the combined data set. Finally, we report on an inverse use of the method, not as guessing the source language of a translated text, but as a tool in quality estimation, marking a text as requiring inspection if it is guessed to be a translation, rather than a text composed originally in the language analysed. We obtain c. 80 % accuracy, comparable to results of earlier work in literary source language guessing—this supports the claim of the method’s validity in identifying salient features of source language interference.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::50b832ffdfc794188a56f2a6447f4367 https://doi.org/10.1007/978-3-319-12069-0_5 Zobrazit plný text záznamu