Unmet Needs and Opportunities for Mobile Translation AI
February 27, 2020 ยท Declared Dead ยท ๐ International Conference on Human Factors in Computing Systems
"No code URL or promise found in abstract"
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Authors
Daniel J. Liebling, Michal Lahav, Abigail Evans, Aaron Donsbach, Jess Holbrook, Boris Smus, Lindsey Boran
arXiv ID
2002.12387
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CY
Citations
97
Venue
International Conference on Human Factors in Computing Systems
Last Checked
2 months ago
Abstract
Translation apps and devices are often presented in the context of providing assistance while traveling abroad. However, the spectrum of needs for cross-language communication is much wider. To investigate these needs, we conducted three studies with populations spanning socioeconomic status and geographic regions: (1) United States-based travelers, (2) migrant workers in India, and (3) immigrant populations in the United States. We compare frequent travelers' perception and actual translation needs with those of the two migrant communities. The latter two, with low language proficiency, have the greatest translation needs to navigate their daily lives. However, current mobile translation apps do not meet these needs. Our findings provide new insights on the usage practices and limitations of mobile translation tools. Finally, we propose design implications to help apps better serve these unmet needs.
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