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Recognizing irregular texts has been a challenging topic in text recognition.To encourage research on this topic, we provide a novel comic onomatopoeiadataset (COO), which consists of onomatopoeia texts in Japanese comics. COO hasmany arbitrary texts, such as extremely curved, partially shrunk texts, orarbitrarily placed texts. Furthermore, some texts are separated into severalparts. Each part is a truncated text and is not meaningful by itself. Theseparts should be linked to represent the intended meaning. Thus, we propose anovel task that predicts the link between truncated texts. We conduct threetasks to detect the onomatopoeia region and capture its intended meaning: textdetection, text recognition, and link prediction. Through extensiveexperiments, we analyze the characteristics of the COO. Our data and code areavailable at \url{https://github.com/ku21fan/COO-Comic-Onomatopoeia}.

COO: Comic Onomatopoeia Dataset for Recognizing Arbitrary or Truncated Texts