CEO: The Linguistic Shortcut
Context:
Your ASR system fails significantly more often for speakers of African American English, causing users to feel "othered" and excluded. You have two years and limited resources to fix the root problem.
Dilemma:
A) Fund a full linguistic study for a genuinely inclusive solution, potentially missing your deadline and risking the project's future.
B) Implement a short-term prompt that asks users to code-switch, raising success rates quickly but forcing accommodation.
Story Behind the Dilemma:
This study investigates the profound psychological and experiential impact of Automated Speech Recognition (ASR) failures on African American users. Moving beyond documented performance gaps, it reveals that recurrent voice errors cause significant harm, leading users to feel “othered” and reinforcing perceptions that the technology was not designed for them. Errors trigger reflections on racial and geographic identity, embedding exclusion into daily digital interactions.
Consequently, African American speakers often engage in linguistic accommodation, consciously altering their speech patterns to be understood by ASR systems—a burden not shared by speakers of mainstream accents. The research argues that simply improving technical accuracy is insufficient; inclusive design must address these negative social-emotional consequences. It advocates for a shift in methodology, recommending deep qualitative approaches like diary studies to center the lived experiences of marginalized communities. By incorporating sociolinguistic insights and community-centered design, developers can build voice systems that are truly responsive to the needs, attitudes, and speech patterns of all users, moving beyond fairness as a metric toward dignity as a goal.
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