Fonts like This but Happier: A New Way to Discover Fonts

Tugba Kulahcioglu, Gerard De Melo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Fonts carry strong emotional and social signals, and can affect user engagement in significant ways. Hence, selecting the right font is a very important step in the design of a multimodal artifact with text. Currently, font exploration is frequently carried out via associated social tags. Users are expected to browse through thousands of fonts tagged with certain concepts to find the one that works best for their use case. In this study, we propose a new multimodal font discovery method in which users provide a reference font together with the changes they wish to obtain in order to get closer to their ideal font. This allows for efficient and goal-driven navigation of the font space, and discovery of fonts that would otherwise likely be missed. We achieve this by learning cross-modal vector representations that connect fonts and query words.

Original languageEnglish (US)
Title of host publicationMM 2020 - Proceedings of the 28th ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery, Inc
Pages2973-2981
Number of pages9
ISBN (Electronic)9781450379885
DOIs
StatePublished - Oct 12 2020
Event28th ACM International Conference on Multimedia, MM 2020 - Virtual, Online, United States
Duration: Oct 12 2020Oct 16 2020

Publication series

NameMM 2020 - Proceedings of the 28th ACM International Conference on Multimedia

Conference

Conference28th ACM International Conference on Multimedia, MM 2020
Country/TerritoryUnited States
CityVirtual, Online
Period10/12/2010/16/20

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction

Keywords

  • multimodal retrieval
  • typography

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