DeepAI AI Chat
Log In Sign Up

Machine Translation of Novels in the Age of Transformer

by   Antonio Toral, et al.

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.


page 1

page 2

page 4

page 7

page 10

page 13

page 15

page 18


What Level of Quality can Neural Machine Translation Attain on Literary Text?

Given the rise of a new approach to MT, Neural MT (NMT), and its promisi...

Scientific Credibility of Machine Translation Research: A Meta-Evaluation of 769 Papers

This paper presents the first large-scale meta-evaluation of machine tra...

Domain-Specific Text Generation for Machine Translation

Preservation of domain knowledge from the source to target is crucial in...

A Snapshot into the Possibility of Video Game Machine Translation

We present in this article what we believe to be one of the first attemp...

Quantitative Fine-Grained Human Evaluation of Machine Translation Systems: a Case Study on English to Croatian

This paper presents a quantitative fine-grained manual evaluation approa...

Explicit Representation of the Translation Space: Automatic Paraphrasing for Machine Translation Evaluation

Following previous work on automatic paraphrasing, we assess the feasibi...

Transformer-based Automatic Post-Editing with a Context-Aware Encoding Approach for Multi-Source Inputs

Recent approaches to the Automatic Post-Editing (APE) research have show...