@inproceedings{Bizzoni2019,
title = {Analyzing variation in translation through neural semantic spaces},
author = {Yuri Bizzoni and Elke Teich},
url = {https://comparable.limsi.fr/bucc2019/Bizzoni_BUCC2019_paper1.pdf},
year = {2019},
date = {2019-08-30},
booktitle = {Special topic: Neural Networks for Building and Using Comparable Corpora, Recent Advances in Natural Language Processing (RANLP), Varna, Bulgaria},
address = {Varna, Bulgaria},
abstract = {We present an approach for exploring the lexical choice patterns in translation on the basis of word embeddings. Specifically, we are interested in variation in translation according to translation mode, i.e. (written) translation vs. (simultaneous) interpreting. While it might seem obvious that the outputs of the two translation modes differ, there are hardly any accounts of the summative linguistic effects of one vs. the other. To explore such effects at the lexical level, we propose a data-driven approach: using neural word embeddings (Word2Vec), we compare the bilingual semantic spaces emanating from source-totranslation and source-to-interpreting.},
pubstate = {published},
type = {inproceedings}
}