Neural machine translation of literary texts from English to Slovene
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Date
2019-08-19Author
Kuzman, Taja
Vintar, Špela
Arčan, Mihael
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Kuzman, Taja , Vintar, Špela , & Arčan, Mihael (2019). Neural machine translation of literary texts from English to Slovene. Paper presented at the Literary Machine Translation Workshop, co-located with Machine Translation Summit 2019, Dublin, Ireland, 19-23 August.
Abstract
Neural Machine Translation has shown
promising performance in literary texts.
Since literary machine translation has not
yet been researched for the English-toSlovene translation direction, this paper
aims to fulfill this gap by presenting a
comparison among bespoke NMT models,
tailored to novels, and Google Neural Machine Translation. The translation models
were evaluated by the BLEU and METEOR metrics, assessment of fluency and
adequacy, and measurement of the postediting effort. The findings show that all
evaluated approaches resulted in an increase in translation productivity. The
translation model tailored to a specific author outperformed the model trained on a
more diverse literary corpus, based on all
metrics except the scores for fluency.
However, the translation model by Google
still outperforms all bespoke models. The
evaluation reveals a very low inter-rater
agreement on fluency and adequacy,
based on the kappa coefficient values, and
significant discrepancies between posteditors. This suggests that these methods
might not be reliable, which should be addressed in future studies.