Building Multimodal Corpora Using Microtask Pipelines and Local Annotators

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.

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