TasvirEt: A Benchmark Dataset for Automatic Turkish Description Generation from Images

Unal, Mesut Erhan
Citamak, Begum
Yagcioglu, Semih
Erdem, Aykut
Erdem, Erkut
Çakıcı, Ruket
Automatically describing images with natural sentences is considered to be a challenging research problem that has recently been explored. Although the number of methods proposed to solve this problem increases over time, since the datasets used commonly in this field contain only English descriptions, the studies have mostly been limited to single language, namely English. In this study, for the first time in the literature, a new dataset is proposed which enables generating Turkish descriptions from images, which can be used as a benchmark for this purpose. Furthermore, two approaches are proposed, again for the first time in the literature, for image captioning in Turkish with the dataset we named as TasvirEt. Our findings indicate that the new Turkish dataset and the approaches used here can be successfully used for automatically describing images in Turkish.
24th Signal Processing and Communication Application Conference (SIU)


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Citation Formats
M. E. Unal et al., “TasvirEt: A Benchmark Dataset for Automatic Turkish Description Generation from Images,” presented at the 24th Signal Processing and Communication Application Conference (SIU), Zonguldak, TURKEY, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55213.