%0 Conference Proceedings %T Automatic Generation of Distractors for Fill-in-the-Blank Exercises with Round-Trip Neural Machine Translation %A Panda, Subhadarshi %A Palma Gomez, Frank %A Flor, Michael %A Rozovskaya, Alla %Y Louvan, Samuel %Y Madotto, Andrea %Y Madureira, Brielen %S Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop %D 2022 %8 May %I Association for Computational Linguistics %C Dublin, Ireland %F panda-etal-2022-automatic %X In a fill-in-the-blank exercise, a student is presented with a carrier sentence with one word hidden, and a multiple-choice list that includes the correct answer and several inappropriate options, called distractors. We propose to automatically generate distractors using round-trip neural machine translation: the carrier sentence is translated from English into another (pivot) language and back, and distractors are produced by aligning the original sentence and its round-trip translation. We show that using hundreds of translations for a given sentence allows us to generate a rich set of challenging distractors. Further, using multiple pivot languages produces a diverse set of candidates. The distractors are evaluated against a real corpus of cloze exercises and checked manually for validity. We demonstrate that the proposed method significantly outperforms two strong baselines. %R 10.18653/v1/2022.acl-srw.31 %U https://aclanthology.org/2022.acl-srw.31 %U https://doi.org/10.18653/v1/2022.acl-srw.31 %P 391-401