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News/Evaluating Bias in Phoneme-Based Automatic Speech Recognition Systems: An Analysis of IPA Transcription Models
arxiv
PublishedJune 11, 2026 at 4:00 AM
—neutral

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

Source
arxiv.orgfull article ↗
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Publisher summary· verbatim

arXiv:2606.11639v1 Announce Type: new Abstract: The popularization of automatic speech recognition (ASR) systems has increased exploration of the demographic biases related to race, age, gender, and accent, often formed from imbalanced training data. Most of these studies focused on standard graphem

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Discussion
Mentioned models
02
  • 01
    WhisperIPA
  • 02
    ZIPA
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#speech recognition#bias#multilingual#open-source

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Mentioned models
02
  • 01
    WhisperIPA
  • 02
    ZIPA
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#speech recognition#bias#multilingual#open-source

Related coverage

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arxivMODF-SIR: A Multi-agent Omni-modal Distilled Framework for Social Intelligence Reasoning18harxivPosition: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!18harxivARGUS: Stacked Multi-View Identity Mosaic Injection for Subject-Preserving Video Generation18harxivGeneralizing Beyond Suboptimality: Offline Reinforcement Learning Learns Effective Scheduling through Random Solutions18h
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