Regression Analysis of Demographic and Technology-Experience Factors Influencing Acceptance of Sign Language Animation

Abstract

Software for automating the creation of linguistically accurate and natural-looking animations of American Sign Language (ASL) could increase information accessibility for many people who are deaf. As compared to recording and updating videos of human ASL signers, technology for automatically producing animation from an easy-to-update script would make maintaining ASL content on websites more efficient. Most sign language animation researchers evaluate their systems by collecting subjective judgments and comprehension-question responses from deaf participants. Through a survey (N = 62) and multiple-regression analysis, we identified relationships between (a) demographic and technology-experience characteristics of participants and (b) the subjective and objective scores collected from them during the evaluation of sign language animation systems. These relationships were experimentally verified in a subsequent user study with 57 participants, which demonstrated that specific subpopulations have higher comprehension or subjective scores when viewing sign language animations in an evaluation study. This finding indicates that researchers should collect and report a set of specific characteristics about participants in any publications describing evaluation studies of their technology, a practice that is not yet currently standard among researchers working in this field. In addition to investigating this relationship between participant characteristics and study results, we have also released our survey questions in ASL and English that can be used to measure these participant characteristics, to encourage reporting of such data in future studies. Such reporting would enable researchers in the field to better interpret and compare results between studies with different participant pools.