Papers by Felix Herron

1 papers
Identifying and typifying demographic unfairness in phoneme-level embeddings of self-supervised speech recognition models (2026.findings-acl)

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Challenge: a number of studies have been done to improve ASR for speaker groups, but there is still room for improvement . authors propose a framework typifying two types of error in phoneme embeddings .
Approach: They propose a framework typifying two types of error that can occur in phoneme modeling . they propose random error/high variance in phonemes embedding vs systematic error/embedding bias .
Outcome: The proposed framework typifies errors in phoneme modeling in ASR systems . it shows that training only on a single, typically disadvantaged SG improves performance .

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