COMICORDA: Dialogue Act Recognition in Comic Books

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F24%3A43972631" target="_blank" >RIV/49777513:23520/24:43972631 - isvavai.cz</a>

Result on the web

<a href="https://aclanthology.org/2024.lrec-main.316/#" target="_blank" >https://aclanthology.org/2024.lrec-main.316/#</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

COMICORDA: Dialogue Act Recognition in Comic Books

Original language description

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.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

ISBN

978-2-493-81410-4

ISSN

2951-2093

e-ISSN

2522-2686

Number of pages

13

Pages from-to

3566-3578

Publisher name

ELRA and ICCL

Place of publication

Paris

Event location

Torino, Italy

Event date

May 20, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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