Evaluating Bias in Phoneme-Based Automatic Speech Recognition Systems: An Analysis of IPA Transcription Models

Excerpt

arXiv:2606.11639v2 Announce Type: replace Abstract: As automatic speech recognition (ASR) systems shift toward multilingual support and low-resource language modeling, phoneme-based layers serve as a critical language-agnostic foundation. However, most evaluations of ASR's demographic biases related to race, age, gender, and accent focus on standard grapheme-based ASR systems with comparatively little emphasis on phoneme-based systems. In this study, we evaluate the performance of WhisperIPA and