Reciprocal Enrichment Between Basque Wikipedia and Machine Translation

The People?s Web Meets NLP: Collaboratively Constructed Language Resources. Springer. 2013.

In this chapter, we define a collaboration framework that enables Wikipedia editors to generate new articles while they help development of Machine Translation (MT) systems by providing post-edition logs. This collaboration framework was tested with editors of Basque Wikipedia. Their post-editing of Computer Science articles has been used to improve the output of a Spanish to Basque MT system called Matxin. For the collaboration between editors and researchers, we selected a set of 100 articles from the Spanish Wikipedia. These articles would then be used as the source texts to be translated into Basque using the MT engine. A group of volunteers from Basque Wikipedia reviewed and corrected the raw MT translations. This collaboration ultimately produced two main benefits: (i) the change logs that would potentially help improve the MT engine by using an automated statistical post-editing system , and (ii) the growth of Basque Wikipedia. The results show that this process can improve the accuracy of an Rule Based MT (RBMT) system in nearly 10% benefiting from the post-edition of 50,000 words in the Computer Science domain. We believe that our conclusions can be extended to MT engines involving other less-resourced languages lacking large parallel corpora or frequently updated lexical knowledge, as well as to other domains.

Download PDF fileDownload from external site