SignUpCrowd: Using Sign-Language as an Input Modality for Microtask Crowdsourcing
Keywords:Crowdsourcing, Input Modality, Microtasks
AbstractDifferent input modalities have been proposed and employed in technological landscapes like microtask crowdsourcing. However, sign language remains an input modality that has received little attention. Despite the fact that thousands of people around the world primarily use sign language, very little has been done to include them in such technological landscapes. We aim to address this gap and take a step towards the inclusion of deaf and mute people in microtask crowdsourcing. We first identify various microtasks which can be adapted to use sign language as input, while elucidating the challenges it introduces. We built a system called ‘SignUpCrowd’ that can be used to support sign language input for microtask crowdsourcing. We carried out a between-subjects study (N=240) to understand the effectiveness of sign language as an input modality for microtask crowdsourcing in comparison to prevalent textual and click input modalities. We explored this through the lens of visual question answering and sentiment analysis tasks by recruiting workers from the Prolific crowdsourcing platform. Our results indicate that sign language as an input modality in microtask crowdsourcing is comparable to the prevalent standards of using text and click input. Although people with no knowledge of sign language found it difficult to use, this input modality has the potential to broaden participation in crowd work. We highlight evidence suggesting the scope for sign language as a viable input type for microtask crowdsourcing. Our findings pave the way for further research to introduce sign language in real-world applications and create an inclusive technological landscape that more people can benefit from.
How to Cite
Singh, A., Wehkamp, S., & Gadiraju, U. (2022). SignUpCrowd: Using Sign-Language as an Input Modality for Microtask Crowdsourcing. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 10(1), 184-194. https://doi.org/10.1609/hcomp.v10i1.21998
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