Paragraph-Level Alignment of an English-Spanish Parallel Corpus of Fiction Texts Using Bilingual Dictionaries

Aligned parallel corpora are very important linguistic resources useful in many text processing tasks such as machine translation, word sense disambiguation, dictionary compilation, etc. Nevertheless, there are few available linguistic resources of this type, especially for fiction texts, due to the difficulties in collecting the texts and high cost of manual alignment. In this paper, we describe an automatically aligned English-Spanish parallel corpus of fiction texts and evaluate our method of alignment that uses linguistic data-namely, on the usage of existing bilingual dictionaries-to calculate word similarity. The method is based on the simple idea: if a meaningful word is present in the source text then one of its dictionary translations should be present in the target text. Experimental results of alignment at paragraph level are described.