arXiv AI
HEAR Who Said What: Unlocking Speaker-Attributed Reasoning via Counterfactual Voice Grounding
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Large Audio Language Models for Spoofing-Aware Speaker Verification
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When Text Misleads: Inconsistent-Aware Reasoning for Audio-Grounded Dialogue
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arXiv AI
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To Trust or Not to Trust: Retrieval-Augmented Fact Checking in Speech
The paper introduces VeriSpeak, a benchmark of 3,879 spoken claims for evaluating fact verification in Large Audio Language Models (LALMs). It shows a clear modality gap: models that verify written claims well often fail on spoken versions, and retrieval alone offers limited improvement. Combining retrieval with explicit reasoning yields the best performance, reaching 86.1% accuracy and demonstrating the need for grounded reasoning over retrieved evidence in speech misinformation detection.
arXiv AI
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Linguistically Augmented Audio Speech Data (LinguAS)
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