A Vietnamese Dataset for Evaluating Machine Reading Comprehension

• URL: http://arxiv.org/abs/2009.14725v3
• Date: Sat, 7 Nov 2020 06:40:46 GMT
• Title: A Vietnamese Dataset for Evaluating Machine Reading Comprehension
• Authors: Kiet Van Nguyen, Duc-Vu Nguyen, Anh Gia-Tuan Nguyen, Ngan Luu-Thuy Nguyen
• Abstract summary: We present UIT-ViQuAD, a new dataset for the low-resource language as Vietnamese to evaluate machine reading comprehension models. This dataset comprises over 23,000 human-generated question-answer pairs based on 5,109 passages of 174 Vietnamese articles from Wikipedia. We conduct experiments on state-of-the-art MRC methods for English and Chinese as the first experimental models on UIT-ViQuAD.
• Score: 2.7528170226206443
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Over 97 million people speak Vietnamese as their native language in the world. However, there are few research studies on machine reading comprehension (MRC) for Vietnamese, the task of understanding a text and answering questions related to it. Due to the lack of benchmark datasets for Vietnamese, we present the Vietnamese Question Answering Dataset (UIT-ViQuAD), a new dataset for the low-resource language as Vietnamese to evaluate MRC models. This dataset comprises over 23,000 human-generated question-answer pairs based on 5,109 passages of 174 Vietnamese articles from Wikipedia. In particular, we propose a new process of dataset creation for Vietnamese MRC. Our in-depth analyses illustrate that our dataset requires abilities beyond simple reasoning like word matching and demands single-sentence and multiple-sentence inferences. Besides, we conduct experiments on state-of-the-art MRC methods for English and Chinese as the first experimental models on UIT-ViQuAD. We also estimate human performance on the dataset and compare it to the experimental results of powerful machine learning models. As a result, the substantial differences between human performance and the best model performance on the dataset indicate that improvements can be made on UIT-ViQuAD in future research. Our dataset is freely available on our website to encourage the research community to overcome challenges in Vietnamese MRC.

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