COMICORDA: Dialogue Act Recognition in Comic Books

Jiri Martinek, Pavel Kral, Ladislav Lenc, Josef Baloun

Abstract
Dialogue act (DA) recognition is usually realized from a speech signal that is transcribed and segmented into text. However, only a little work in DA recognition from images exists. Therefore, this paper concentrates on this modality and presents a novel DA recognition approach for image documents, namely comic books. To the best of our knowledge, this is the first study investigating dialogue acts from comic books and represents the first steps to building a model for comic book understanding. The proposed method is composed of the following steps: speech balloon segmentation, optical character recognition (OCR), and DA recognition itself. We use YOLOv8 for balloon segmentation, Google Vision for OCR, and Transformer-based models for DA classification. The experiments are performed on a newly created dataset comprising 1,438 annotated comic panels. It contains bounding boxes, transcriptions, and dialogue act annotation. We have achieved nearly 98% average precision for speech balloon segmentation and exceeded the accuracy of 70% for the DA recognition task. We also present an analysis of dialogue structure in the comics domain and compare it with the standard DA datasets, representing another contribution of this paper.
Anthology ID:
2024.lrec-main.316
Volume:
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Venues:
LREC | COLING
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
3566–3578
Language:
URL:
https://aclanthology.org/2024.lrec-main.316
DOI:
Bibkey:
Cite (ACL):
Jiri Martinek, Pavel Kral, Ladislav Lenc, and Josef Baloun. 2024. COMICORDA: Dialogue Act Recognition in Comic Books. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 3566–3578, Torino, Italia. ELRA and ICCL.
Cite (Informal):
COMICORDA: Dialogue Act Recognition in Comic Books (Martinek et al., LREC-COLING 2024)
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https://preview.aclanthology.org/nschneid-patch-2/2024.lrec-main.316.pdf
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