Following the Trail of Source Languages in Literary Translations - VOGEL, CARL (Springer, 2014)
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 in- spection if it is guessed to be a translation, rather than a text composed originally in the language analysed. With 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.
Research and Development in Intelligent Systems XXXI
PUBLISHED
Proceedings of AI-2014, The Thirty-fourth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
Heidelberg
Keywords: computational linguistics; stylistics; stylometry; machine learning; text classification; translation effects; Creative Technologies; Digital Humanities; Intelligent Content & Communications; Computational linguistics; Language and/or Literature, Translation; MACHINE LEARNING; Translation theory and practice; stylistics; stylometry