Polygloss - A conversational agent for language practice
Etiene da Cruz Dalcol, Massimo Poesio · Linköping electronic conference proceedings · 2020
This paper explores the impact on language proficiency of comprehensible output applied in computer assisted language learning (CALL).Targeting speakers of intermediate level, we adapted a visually-grounded dialogue task, optimizing for language acquisition.The task was implemented as a mobile application where learners are organized in pairs and write short texts to play an imageguessing game, producing samples in a wide variety of languages.Following a framework for CALL evaluation, we conducted an analysis of the game and players' gains through time, including the measure of pre-trained XLM-r cross-lingual transformers' acceptability score of the samples.The results confirm the intended fit for intermediate speakers as well as reveal possible benefits for other levels.This research provides a successful case study of a multilingual CALL design where users have the autonomy to generate output creatively.