Translating literary text between related languages using SMT
Toral, AntonioORCID: 0000-0003-2357-2960 and Way, AndyORCID: 0000-0001-5736-5930
(2015)
Translating literary text between related languages using SMT.
In: Fourth Workshop on Computational Linguistics for Literature, 4 June 2015, Denver, CO, USA.
We explore the feasibility of applying machine
translation (MT) to the translation of literary
texts. To that end, we measure the translatability of literary texts by analysing parallel
corpora and measuring the degree of freedom
of the translations and the narrowness of the
domain. We then explore the use of domain
adaptation to translate a novel between two related languages, Spanish and Catalan. This
is the first time that specific MT systems are
built to translate novels. Our best system outperforms a strong baseline by 4.61 absolute
points (9.38% relative) in terms of BLEU and
is corroborated by other automatic evaluation
metrics. We provide evidence that MT can
be useful to assist with the translation of novels between closely-related languages, namely
(i) the translations produced by our best system are equal to the ones produced by a professional human translator in almost 20% of
cases with an additional 10% requiring at most
5 character edits, and (ii) a complementary human evaluation shows that over 60% of the
translations are perceived to be of the same (or
even higher) quality by native speakers.
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Funders:
European Union Seventh Framework Programme FP7/2007-2013 under grant agreement PIAP-GA-2012-324414 (AbuMaTran), Science Foundation Ireland through the CNGL Programme (Grant 12/CE/I2267) in the ADAPT Centre (www.adaptcentre.ie) at Dublin City University.
ID Code:
23221
Deposited On:
01 May 2019 15:32 by
Thomas Murtagh
. Last Modified 01 May 2019 15:32