Image Description Dataset for Language Learners
Kento Tanaka | Taichi Nishimura | Hiroaki Nanjo | Keisuke Shirai | Hirotaka Kameko | Masatake Dantsuji
Proceedings of the Thirteenth Language Resources and Evaluation Conference
We focus on image description and a corresponding assessment system for language learners. To achieve automatic assessment of image description, we construct a novel dataset, the Language Learner Image Description (LLID) dataset, which consists of images, their descriptions, and assessment annotations. Then, we propose a novel task of automatic error correction for image description, and we develop a baseline model that encodes multimodal information from a learner sentence with an image and accurately decodes a corrected sentence. Our experimental results show that the developed model can revise errors that cannot be revised without an image.