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Based on the theoretical and methodological framework of Corpus Linguistics (CL), and allied to Natural Language Processing (NLP) techniques, we present a lexicostatistical study about textual productions written by students of Portuguese as an additional language. We begin by discussing the relevance of quantitative language studies, specially regarding word frequencies, as proposed by Biderman (1978, 1996) and Hoffmann (2007). Then, we situate CL and NLP and their role in the proposition of a methodology (EVERS, 2013) for automatic essay score applied to texts produced in the context of Celpe-Bras - a Brazilian Portuguese as an additional language proficiency exam. By using supervised Machine Learning (ML), a NLP technique, it was possible to identify lexical cohesive patterns and distinguish levels of proficiency using such patterns. Cohesion, coherence and intelligibility parameters were used and the text sample was submitted for examination. At the end, the proposed methodology combines CL and NLP and it is problematized: we point out limits, advantages and future applications for the results found with this research.

Linguística de Corpus, Léxico-Estatística Textual e Processamento de Linguagem Natural: perspectiva para estudos de vocabulário em produções textuais