Fairness Beyond a Single Run: Training-Seed Variability in Speech LLM Adaptation

arXiv:2609.38976 · cs.CL · Submitted 2026-09-30 · Read on arXiv

cs.CL

Submitted: 2026-09-30

Updated: 2026-09-30

Terminology

• Accuracy — 8× in this paper · explained in 1 episode
• Adaptation — 7× in this paper · explained in 1 episode
• Benchmarking — 4× in this paper · explained in 4 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Domain Shift — 1× in this paper · explained in 4 episodes
• LoRA Adapters — 1× in this paper · explained in 3 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes

Sources

• Seeds Before Objectives: Rethinking Evaluation for Low-Resource Garhwali ASR
• The Voice of Equity: A Systematic Evaluation of Bias Mitigation Techniques for Speech-Based Cognitive Impairment Detection Across Architectures and Demographics
• Toward Fair Speech Technologies: A Comprehensive Survey of Bias and Fairness in Speech AI
• Do LLM Decoders Listen Fairly? Benchmarking How Language Model Priors Shape Bias in Speech Recognition
• Granite-speech: open-source speech-aware LLMs with strong English ASR capabilities

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