Unmet Needs and Opportunities for Mobile Translation AI
Daniel J. Liebling, Michal Lahav, Abigail Evans, Aaron Donsbach, Jess Holbrook, Boris Smus, Lindsey Boran
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.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext fd35dfe3-e0ca-4d81-bed5-e0611ca55323Cited by top-tier papers10
- Angler: Helping Machine Translation Practitioners Prioritize Model ImprovementsSamantha Robertson, Zijie J. Wang, Dominik Moritz, Mary Beth Kery et al.CHI 2023 · 20 citations
- Trkic G00gle: Why and How Users Game Translation AlgorithmsSoomin Kim, Changhoon Oh, Won-Ik Cho, Donghoon Shin et al.CSCW 2021 · 10 citations
- A case for "little English" in Nurse Notes from the Telehealth Intervention Program for Seniors: Implications for Future Design and ResearchVeena Calambur, Dongwhan Jun, Melody K. Schiaffino, Zhan Zhang et al.CHI 2024 · 3 citations
- A Conditional Companion: Lived Experiences of People with Mental Health Disorders Using LLMs: Conditional Companion: LLMs & Mental HealthAditya Kumar Purohit, Hendrik HeuerCHI 2026 · 3 citations
- ChatLearn: Leveraging Non-Native Speaker Communication Challenges as Language Learning OpportunitiesPeinuan Qin, Yugin Tan, Jingzhu Chen, Nattapat Boonprakong et al.CHI 2026 · 2 citations
Related papers
- An Interdisciplinary Approach to Human-Centered Machine TranslationMarine Carpuat, Omri Asscher, Kalika Bali, Luisa Bentivogli et al.EMNLP 2025 · 2 citations
- Exploring the Experiences of Individuals Who are Blind or Low-Vision Using Object-Recognition Technologies in IndiaGesu India, Simon Robinson, Jennifer Pearson, Cecily Morrison et al.CHI 2025 · 8 citations
- Understanding the Benefits and Design of Chatbots to Meet the Healthcare Needs of Migrant WorkersYuan-Chi Tseng, Weerachaya Jarupreechachan, Tuan-He LeeCSCW 2023 · 28 citations
- Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect TranslationsYimin Xiao, Yongle Zhang, Dayeon Ki, Calvin Bao et al.EMNLP 2025
- Envisioning Support-Centered Technologies for Language Practice and Use: Needs and Design Opportunities for Immigrant English Language Learners (ELLs)Adinawa Adjagbodjou, Geoff KaufmanCHI 2024 · 14 citations
