Study reveals ASR bias against Newcastle English dialect

A new study published on arXiv analyzes bias in Automatic Speech Recognition (ASR) systems, focusing on Newcastle English. Researchers found that state-of-the-art ASR systems exhibit significant transcription errors when processing this regional dialect, with over 3,000 errors identified. The analysis revealed that these errors are not random but are socially patterned, often linked to dialect-specific phonological features, vocabulary, and grammar, and disproportionately affect men and speakers at the extremes of the age spectrum. The findings underscore the need for greater attention to dialectal variation and community-specific speech data in the development and evaluation of ASR technologies to ensure more equitable performance. AI

IMPACT Highlights the need for more inclusive ASR development to avoid marginalizing speakers of regional dialects.

RANK_REASON Academic paper analyzing bias in speech recognition technology. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

• arXiv
• Diachronic Electronic Corpus of Tyneside English
• Hugging Face
• Kevin Tang
• Newcastle English
• North East England

• paper
• other

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