Automated question generation and question answering from Turkish texts using text-to-text transformers

• URL: http://arxiv.org/abs/2111.06476v1
• Date: Thu, 11 Nov 2021 22:00:45 GMT
• Title: Automated question generation and question answering from Turkish texts using text-to-text transformers
• Authors: Fatih Cagatay Akyon, Devrim Cavusoglu, Cemil Cengiz, Sinan Onur Altinuc, Alptekin Temizel
• Abstract summary: We fine-tune a multilingual T5 (mT5) transformer in a multi-task setting for QA, QG and answer extraction tasks. This is the first academic work that attempts to perform automated text-to-text question generation from Turkish texts.
• Score: 1.5749416770494706
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: While exam-style questions are a fundamental educational tool serving a variety of purposes, manual construction of questions is a complex process that requires training, experience and resources. To reduce the expenses associated with the manual construction of questions and to satisfy the need for a continuous supply of new questions, automatic question generation (QG) techniques can be utilized. However, compared to automatic question answering (QA), QG is a more challenging task. In this work, we fine-tune a multilingual T5 (mT5) transformer in a multi-task setting for QA, QG and answer extraction tasks using a Turkish QA dataset. To the best of our knowledge, this is the first academic work that attempts to perform automated text-to-text question generation from Turkish texts. Evaluation results show that the proposed multi-task setting achieves state-of-the-art Turkish question answering and question generation performance over TQuADv1, TQuADv2 datasets and XQuAD Turkish split. The source code and pre-trained models are available at https://github.com/obss/turkish-question-generation.

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