Languages use different lexical inventories to encode information, ranging from small sets of simplex words to large sets of morphologically complex words. Grammaticalization theories argue that this variation arises as the outcome of diachronic processes whereby co-occurring words merge to one word and build up complex morphology. To model these processes we present a) a quantitative measure o...

Children who hear large amounts of diverse speech learn language more quickly than children who do not. However, high correlations between the amount and the diversity of the input in speech samples makes it difficult to isolate the influence of each. We overcame this problem by controlling the input to a computational model so that amount of exposure to linguistic input (quantity) and the qual...

Neural machine translation systems have revolutionized processes in terms of quantity and speed recent years, they even been claimed to achieve human parity. However, the quality their output has also raised serious doubts concerns, such as loss lexical variation, evidence “machine translationese”, its effect on post-editing, which results “post-editese”. In this study, we analyze outputs three...

TGermaCorp is a German text corpus whose primary sources are collected from German literature texts which date from the sixteenth century to the present. The corpus is intended to represent its target language (German) in syntactic, lexical, stylistic and chronological diversity. For this purpose, it is hand-annotated on several linguistic layers, including POS, lemma, named entities, multiword...