New study tests machine learning on detection of borrowed words in world languages

IMAGE: Lexical borrowing is very widespread and may affect even those words that play an important role in our daily life. English'mountain', for example, was borrowed from Old French, along... view more Lexical borrowing, or the direct transfer of words from one language to another, has interested scholars for millennia, as evidenced already in Plato's Kratylos dialogue, in which Socrates discusses the challenge imposed by borrowed words on etymological studies. In historical linguistics, lexical borrowings help researchers trace the evolution of modern languages and indicate cultural contact between distinct linguistic groups - whether recent or ancient. However, the techniques for identifying borrowed words have resisted formalization, demanding that researchers rely on a variety of proxy information and the comparison of multiple languages. "The automated detection of lexical borrowings is still one of the most difficult tasks we face in computational historical linguistics," says Johann-Mattis List, who led the study. In the current study, researchers from PUCP and MPI-SHH employed different machine learning techniques to train language models that mimic the way in which linguists identify borrowings when considering only the evidence provided by a single language: if sounds or the ways in which sounds combine to form words are atypical when comparing them with other words in the same language, this often hints to recent borrowings.