At a Different Pace: Evaluating Whether Users Prefer Timing Parameters in American Sign Language Animations to Differ from Human Signers' Timing

Sedeeq Al-Khazraji, Becca Dingman, Sooyeon Lee, Matt Huenerfauth

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

11 Scopus citations

Abstract

Adding American Sign Language (ASL) versions of information content to websites can improve information accessibility for many people who are Deaf or Hard of Hearing (DHH) who may have lower levels of English literacy. Generating animations from a script representation would enable this content to be easily updated, yet software is needed that can set detailed speed and timing parameters for such animations, which prior work has revealed to be critical for their understandability and acceptance among DHH users. Despite recent work on predicting these parameters using AI models trained on recordings of human signers, no prior work had examined whether DHH users actually prefer for these speed and timing properties to be similar to humans, or to be exaggerated, e.g. for additional clarity. We conducted two empirical studies to investigate preferences of ASL signers for speed and timing parameters of ASL animations, including: Sign duration, transition time, differential signing rate, pause length, and pausing frequency. Our first study (N=20) identified two preferred values from among five options for each parameter, one of which included a typical human value for this parameter, and a second study (N=20) identified the most preferred value. We found that while ASL signers preferred pause length and frequency to be similar to those of humans, they actually preferred animations to have faster signs, slower transitions, and less dynamic variation in differential signing speed, as compared to the timing of human signers. This study provides specific empirical guidance for creators of future ASL animation technologies, and more broadly, it demonstrates that it is not safe to assume that ASL signers will simply prefer for properties of ASL animations to be as similar as possible to human signers.

Original languageEnglish (US)
Title of host publicationASSETS 2021 - 23rd International ACM SIGACCESS Conference on Computers and Accessibility
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450383066
DOIs
StatePublished - Oct 17 2021
Externally publishedYes
Event23rd International ACM SIGACCESS Conference on Computers and Accessibility, ASSETS 2021 - Virtual, Online, United States
Duration: Oct 18 2021Oct 22 2021

Publication series

NameASSETS 2021 - 23rd International ACM SIGACCESS Conference on Computers and Accessibility

Conference

Conference23rd International ACM SIGACCESS Conference on Computers and Accessibility, ASSETS 2021
Country/TerritoryUnited States
CityVirtual, Online
Period10/18/2110/22/21

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Computer Graphics and Computer-Aided Design

Keywords

  • ASL
  • American Sign Language
  • Animation
  • Modeling.
  • Prosodic Breaks
  • Speed
  • Timing

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