Machine Translation of Novels in the Age of Transformer

• URL: http://arxiv.org/abs/2011.14979v1
• Date: Mon, 30 Nov 2020 16:51:08 GMT
• Title: Machine Translation of Novels in the Age of Transformer
• Authors: Antonio Toral, Antoni Oliver, Pau Ribas Ballest\'in
• Abstract summary: We build a machine translation system tailored to the literary domain, specifically to novels, based on the state-of-the-art architecture in neural MT (NMT), the Transformer, for the translation direction English-to-Catalan. We compare this MT system against three other systems (two domain-specific systems under the recurrent and phrase-based paradigms and a popular generic on-line system) on three evaluations. As expected, the domain-specific Transformer-based system outperformed the three other systems in all the three evaluations conducted, in all cases by a large margin.
• Score: 1.6453685972661827
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this chapter we build a machine translation (MT) system tailored to the literary domain, specifically to novels, based on the state-of-the-art architecture in neural MT (NMT), the Transformer (Vaswani et al., 2017), for the translation direction English-to-Catalan. Subsequently, we assess to what extent such a system can be useful by evaluating its translations, by comparing this MT system against three other systems (two domain-specific systems under the recurrent and phrase-based paradigms and a popular generic on-line system) on three evaluations. The first evaluation is automatic and uses the most-widely used automatic evaluation metric, BLEU. The two remaining evaluations are manual and they assess, respectively, preference and amount of post-editing required to make the translation error-free. As expected, the domain-specific Transformer-based system outperformed the three other systems in all the three evaluations conducted, in all cases by a large margin.

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