Search Results for author: Tuomo Hiippala

Found 8 papers, 2 papers with code

Developing a tool for fair and reproducible use of paid crowdsourcing in the digital humanities

2 code implementations LaTeCHCLfL (COLING) 2022 Tuomo Hiippala, Helmiina Hotti, Rosa Suviranta

This system demonstration paper describes ongoing work on a tool for fair and reproducible use of paid crowdsourcing in the digital humanities.

Applied Language Technology: NLP for the Humanities

no code implementations NAACL (TeachingNLP) 2021 Tuomo Hiippala

This contribution describes a two-course module that seeks to provide humanities majors with a basic understanding of language technology and its applications using Python.

Semiotically-grounded distant viewing of diagrams: insights from two multimodal corpora

no code implementations8 Mar 2021 Tuomo Hiippala, John A. Bateman

In this article, we bring together theories of multimodal communication and computational methods to study how primary school science diagrams combine multiple expressive resources.

Position Vocal Bursts Valence Prediction

Introducing the diagrammatic semiotic mode

no code implementations30 Jan 2020 Tuomo Hiippala, John A. Bateman

As the use and diversity of diagrams across many disciplines grows, there is an increasing interest in the diagrams research community concerning how such diversity might be documented and explained.

General Classification

AI2D-RST: A multimodal corpus of 1000 primary school science diagrams

no code implementations9 Dec 2019 Tuomo Hiippala, Malihe Alikhani, Jonas Haverinen, Timo Kalliokoski, Evanfiya Logacheva, Serafina Orekhova, Aino Tuomainen, Matthew Stone, John A. Bateman

This article introduces AI2D-RST, a multimodal corpus of 1000 English-language diagrams that represent topics in primary school natural sciences, such as food webs, life cycles, moon phases and human physiology.

Question Answering Visual Question Answering

Classifying Diagrams and Their Parts using Graph Neural Networks: A Comparison of Crowd-Sourced and Expert Annotations

no code implementations5 Dec 2019 Tuomo Hiippala

This article compares two multimodal resources that consist of diagrams which describe topics in elementary school natural sciences.

Representation Learning

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