ArticleFrontiers in artificial intelligence2021
"I don't Think These Devices are Very Culturally Sensitive."-Impact of Automated Speech Recognition Errors on African Americans.
Article in Frontiers in artificial intelligence, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed, 102 citations in OpenAlex.
- Current challenges for global equity related to the implementation of artificial intelligence in pediatric imaging.Pediatric radiology · 2026Review
- Assessing the Reliability, Accuracy, and Relevance of Artificial Intelligence Speech Recognition for Clinical Documentation: A Scoping Review.Journal of evaluation in clinical practice · 2026Article
- "I Don't Trust it, but I Use it": Navigating Trust, Privacy, and Identity in Disabled People's Use of Generative AI.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2026Article
- Phonological complexity, speech style, and individual differences influence ASR performance for Tarifit.Scientific reports · 2026Article
- Voice-Assisted Technology for People With Parkinson's Disease Experiencing Speech and Voice Difficulties: Co-Designing Solutions Using Design Thinking.JMIR rehabilitation and assistive technologies · 2026Article
- Demographic and Acoustic Factors related to Automatic Speech Recognition Inaccuracies for Child African American English Speakers.Perspectives of the ASHA special interest groups · 2025Article
- Exploring Speech and Language Therapists' Perspectives of Voice-Assisted Technology as a Tool for Dysarthria: Qualitative Study.JMIR rehabilitation and assistive technologies · 2025Article
- Exploring the Perceptions of Voice-Assisted Technology as a Tool for Speech and Voice Difficulties: Focus Group Study Among People With Parkinson Disease and Their Carers.JMIR rehabilitation and assistive technologies · 2025Article
- Article
- How People Living With Amyotrophic Lateral Sclerosis Use Personalized Automatic Speech Recognition Technology to Support Communication.Journal of speech, language, and hearing research : JSLHR · 2024Article
- STELA: a community-centred approach to norm elicitation for AI alignment.Scientific reports · 2024Article
- Cultivation of human centered artificial intelligence: culturally adaptive thinking in education (CATE) for AI.Frontiers in artificial intelligence · 2023Article
- Voice-Assisted Technology as a Potential Tool for Addressing Speech and Voice Concerns Experienced by People With Parkinson's Disease and Other Conditions Presenting With Dysarthria: A Scoping Review.International journal of language & communication disordersArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Automated speech recognition (ASR) converts language into text and is used across a variety of applications to assist us in everyday life, from powering virtual assistants, natural language conversations, to enabling dictation services. While recent work suggests that there are racial disparities in the performance of ASR systems for speakers of African American Vernacular English, little is known about the psychological and experiential effects of these failures paper provides a detailed examination of the behavioral and psychological consequences of ASR voice errors and the difficulty African American users have with getting their intents recognized. The results demonstrate that ASR failures have a negative, detrimental impact on African American users. Specifically, African Americans feel othered when using technology powered by ASR-errors surface thoughts about identity, namely about race and geographic location-leaving them feeling that the technology was not made for them. As a result, African Americans accommodate their speech to have better success with the technology. We incorporate the insights and lessons learned from sociolinguistics in our suggestions for linguistically responsive ways to build more inclusive voice systems that consider African American users' needs, attitudes, and speech patterns. Our findings suggest that the use of a diary study can enable researchers to best understand the experiences and needs of communities who are often misunderstood by ASR. We argue this methodological framework could enable researchers who are concerned with fairness in AI to better capture the needs of all speakers who are traditionally misheard by voice-activated, artificially intelligent (voice-AI) digital systems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.