Building Multimodal Corpora Using Microtask Pipelines and Local Annotators

Helmiina Hotti, Raul Vazquez, Anna-Kaisa Jokipohja, Timo Kalliokoski, Henna Paakki, Rosa Suviranta, Tuomo Hiippala


Abstract
Multimodality, or how human communication and interaction combine multiple forms of expression, is studied across diverse fields of research. Many of these fields have underlined the need for large, richly annotated multimodal corpora to support empirical research. While language resources are increasingly annotated using microtask crowdsourcing, multimodal corpora remain largely reliant on expert annotators, which creates a bottleneck for scalability and broad applicability. This paper presents a novel hybrid approach to multimodal corpus annotation, leveraging the efficiency of microtask pipelines while preserving theoretical rigour. Our approach decomposes the annotation process into sequences of simple, well-instructed tasks, which are then performed by locally recruited non-expert annotators. We demonstrate the feasibility of this approach by presenting a pipeline for annotating the multimodal structure of school textbooks.
Anthology ID:
2026.lrec-1.514
Volume:
Proceedings of the Fifteenth Language Resources and Evaluation Conference
Month:
May
Year:
2026
Address:
Palma de Mallorca, Spain
Editors:
Stelios Piperidis, Núria Bel, Henk van den Heuvel, Nancy Ide, Simon Krek, Antonio Toral
Venue:
LREC
SIG:
Publisher:
ELRA Language Resource Association
Note:
Pages:
6483–6495
Language:
External URL:
https://lrec.elra.info/lrec2026-main-514
DOI:
10.63317/434uxg6yj2aj
Bibkey:
Cite (ACL):
Helmiina Hotti, Raul Vazquez, Anna-Kaisa Jokipohja, Timo Kalliokoski, Henna Paakki, Rosa Suviranta, and Tuomo Hiippala. 2026. Building Multimodal Corpora Using Microtask Pipelines and Local Annotators. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 6483–6495, Palma de Mallorca, Spain. ELRA Language Resource Association.
Cite (Informal):
Building Multimodal Corpora Using Microtask Pipelines and Local Annotators (Hotti et al., LREC 2026)
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