This study explores the potential benefits of a recently proposed transformer-based multi-task Natural Language Understanding (NLU) architecture, mainly to perform Intent Recognition on small-size domain-specific educational game datasets. The evaluation datasets were collected from children practicing basic math concepts via play-based interactions in game-based learning settings.
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