Unmet Needs and Opportunities for Mobile Translation AI
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Abstract (arXiv)
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.
Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Feb 2020.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 0; 2025: 7; 2026: 2.
14 papers.
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- 2021Gender Bias in Machine Translationcited by 116
- 2023Angler: Helping Machine Translation Practitioners Prioritize Model Improvementscited by 11
- 2025Translation in the Hands of Many:Centering Lay Users in Machine Translation Interactionscited by 8
- 2025An Interdisciplinary Approach to Human-Centered Machine Translationcited by 6
- 2023Towards cross-language prosody transfer for dialogcited by 5
- 2025Should I Share this Translation? Evaluating Quality Feedback for User Reliance on Machine Translationcited by 5
- 2025Spatial Speech Translation: Translating Across Space With Binaural Hearablescited by 3
- 2022Beyond General Purpose Machine Translation: The Need for Context-specific Empirical Research to Design for Appropriate User Trustcited by 1
- 2025Sociotechnical Effects of Machine Translationcited by 1
- 2025Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translationscited by 1
- 2026A Conditional Companion: Lived Experiences of People with Mental Health Disorders Using LLMscited by 1
- 2022Learnings from Technological Interventions in a Low Resource Language: Enhancing Information Access in Gondicited by 0
- 2026Measuring User's Mental Models of Speech Translation in Human-AI Collaboration23 Jun 2026
- 2026A Conditional Companion: Lived Experiences of People with Mental Health Disorders Using LLMs30 Jan 2026
- 2025Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translations11 Oct 2025
- 2025Toward Machine Interpreting: Lessons from Human Interpreting Studies11 Aug 2025
- 2025An Interdisciplinary Approach to Human-Centered Machine Translation16 Jun 2025
- 2025Should I Share this Translation? Evaluating Quality Feedback for User Reliance on Machine Translation30 May 2025
- 2025Spatial Speech Translation: Translating Across Space With Binaural Hearables25 Apr 2025
- 2025Sociotechnical Effects of Machine Translation26 Mar 2025
- 2025Translation in the Hands of Many:Centering Lay Users in Machine Translation Interactions19 Feb 2025
- 2023Towards cross-language prosody transfer for dialog9 Jul 2023
- 2023Angler: Helping Machine Translation Practitioners Prioritize Model Improvements12 Apr 2023
- 2022Learnings from Technological Interventions in a Low Resource Language: Enhancing Information Access in Gondi29 Nov 2022
- 2021Gender Bias in Machine Translationcited by 116
- 2023Angler: Helping Machine Translation Practitioners Prioritize Model Improvementscited by 11
- 2025Translation in the Hands of Many:Centering Lay Users in Machine Translation Interactionscited by 8
- 2025An Interdisciplinary Approach to Human-Centered Machine Translationcited by 6
- 2023Towards cross-language prosody transfer for dialogcited by 5
- 2025Should I Share this Translation? Evaluating Quality Feedback for User Reliance on Machine Translationcited by 5
- 2025Spatial Speech Translation: Translating Across Space With Binaural Hearablescited by 3
- 2022Beyond General Purpose Machine Translation: The Need for Context-specific Empirical Research to Design for Appropriate User Trustcited by 1
- 2025Sociotechnical Effects of Machine Translationcited by 1
- 2025Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translationscited by 1
- 2026A Conditional Companion: Lived Experiences of People with Mental Health Disorders Using LLMscited by 1
- 2022Learnings from Technological Interventions in a Low Resource Language: Enhancing Information Access in Gondicited by 0
12 most cited of 14 All 14 (JSON)
- 2026Measuring User's Mental Models of Speech Translation in Human-AI Collaboration23 Jun 2026
- 2026A Conditional Companion: Lived Experiences of People with Mental Health Disorders Using LLMs30 Jan 2026
- 2025Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translations11 Oct 2025
- 2025Toward Machine Interpreting: Lessons from Human Interpreting Studies11 Aug 2025
- 2025An Interdisciplinary Approach to Human-Centered Machine Translation16 Jun 2025
- 2025Should I Share this Translation? Evaluating Quality Feedback for User Reliance on Machine Translation30 May 2025
- 2025Spatial Speech Translation: Translating Across Space With Binaural Hearables25 Apr 2025
- 2025Sociotechnical Effects of Machine Translation26 Mar 2025
- 2025Translation in the Hands of Many:Centering Lay Users in Machine Translation Interactions19 Feb 2025
- 2023Towards cross-language prosody transfer for dialog9 Jul 2023
- 2023Angler: Helping Machine Translation Practitioners Prioritize Model Improvements12 Apr 2023
- 2022Learnings from Technological Interventions in a Low Resource Language: Enhancing Information Access in Gondi29 Nov 2022
12 newest of 14 All 14 (JSON)