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TREN is an application that provides researchers with an interactive environment for the semi-automatic annotation and analysis of Turkish–English code-switching data, particularly targeting intra-word code-switching and morphologically glossed corpus creation.
This project uses existing open-source eye-tracking data from Mandarin Chinese-English bilinguals to train a machine learning model to predict L2 English Language Proficiency based on reading behavior.