Unmet Needs and Opportunities for Mobile Translation AI

要旨

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.

キーワード
machine translation
mobile
migrants
immigrants
emerging markets
speech
著者
Daniel J. Liebling
Google, Seattle, WA, USA
Michal Lahav
Google, Seattle, WA, USA
Abigail Evans
Northeastern University, Seattle, WA, USA
Aaron Donsbach
Google, Seattle, WA, USA
Jess Holbrook
Google, Seattle, WA, USA
Boris Smus
Google, Seattle, WA, USA
Lindsey Boran
Google, Mountain View, CA, USA
DOI

10.1145/3313831.3376261

論文URL

https://doi.org/10.1145/3313831.3376261

会議: CHI 2020

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)

セッション: On the phone

Paper session
317AB KAHO'OLAWE
5 件の発表
2020-04-28 01:00:00
2020-04-28 02:15:00
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