The study of the biological foundations of language is sometimes called biolinguistics. This particular term finds its historical origins in the 1950s, and for various reasons it has also gained considerable traction in recent years. While its increasing use apparently signals an equally increasing interest in biology, apart from a few exceptions not much is added to and beyond standard linguistic theorizing by those linguists who use it, resulting in a complex and confusing literature.

Machine translation (MT) has become increasingly important and popular in the past decade, leading to the development of MT evaluation metrics aiming at automatically assessing MT output. Most of these metrics use reference translations to compare systems output, therefore, they should not only detect MT errors but also be able to identify correct equivalent expressions so as not to penalize them when those are not displayed in the reference translations.

At present, automatic discourse analysis is a relevant research topic in the field of NLP. However, discourse is one of the phenomena most difficult to process. Although discourse parsers have been already developed for several languages, this tool does not exist for Catalan. In order to implement this kind of parser, the first step is to develop a discourse segmenter. In this article we present the first discourse segmenter for texts in Catalan.