"It's not a representation of me": Examining Accent Bias and Digital
  Exclusion in Synthetic AI Voice Services
Recent advances in artificial intelligence (AI) speech generation and voice
cloning technologies have produced naturalistic speech and accurate voice
replication, yet their influence on sociotechnical systems across diverse
accents and linguistic traits is not fully understood. This study evaluates two
synthetic AI voice services (Speechify and ElevenLabs) through a mixed methods
approach using surveys and interviews to assess technical performance and
uncover how users' lived experiences influence their perceptions of accent
variations in these speech technologies. Our findings reveal technical
performance disparities across five regional, English-language accents and
demonstrate how current speech generation technologies may inadvertently
reinforce linguistic privilege and accent-based discrimination, potentially
creating new forms of digital exclusion. Overall, our study highlights the need
for inclusive design and regulation by providing actionable insights for
developers, policymakers, and organizations to ensure equitable and socially
responsible AI speech technologies.
67fe7287ebac3e14798967e0
Shira Michel
extracted_confirmed
2025-04-15T15:04:12.728Z
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Shira Michel
user
shiramichel
67fe7287ebac3e14798967e1
Sufi Kaur
67fe7287ebac3e14798967e2
Sarah Elizabeth Gillespie
67fe7287ebac3e14798967e3
Jeffrey Gleason
67fe7287ebac3e14798967e4
Christo Wilson
67fe7287ebac3e14798967e5
Avijit Ghosh
claimed_verified
2025-04-18T09:40:28.482Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/6413251362e6057cbb6259bd/k8UMg_tnorG_uCXidybZ7.jpeg
Avijit Ghosh
user
evijit
"It's not a representation of me": Examining Accent Bias and Digital
  Exclusion in Synthetic AI Voice Services
Recent advances in artificial intelligence (AI) speech generation and voice
cloning technologies have produced naturalistic speech and accurate voice
replication, yet their influence on sociotechnical systems across diverse
accents and linguistic traits is not fully understood. This study evaluates two
synthetic AI voice services (Speechify and ElevenLabs) through a mixed methods
approach using surveys and interviews to assess technical performance and
uncover how users' lived experiences influence their perceptions of accent
variations in these speech technologies. Our findings reveal technical
performance disparities across five regional, English-language accents and
demonstrate how current speech generation technologies may inadvertently
reinforce linguistic privilege and accent-based discrimination, potentially
creating new forms of digital exclusion. Overall, our study highlights the need
for inclusive design and regulation by providing actionable insights for
developers, policymakers, and organizations to ensure equitable and socially
responsible AI speech technologies.
Evaluation of AI speech services shows performance disparities across accents, possibly reinforcing linguistic privilege and digital exclusion, emphasizing the need for inclusive design and regulation.
AI speech generation voice cloning naturalistic speech voice replication sociotechnical systems regional accents linguistic traits technical performance accent variations linguistic privilege accent-based discrimination digital exclusion inclusive design regulation