Beyond Transcription: Unified Audio Schema for Perception-Aware AudioLLMs
Recent Audio Large Language Models (AudioLLMs) exhibit a striking performance inversion: while excelling at complex reasoning tasks, they consistently underperform on fine-grained acoustic perception. We attribute this gap to a fundamental limitation of ASR-centric training, which provides precise linguistic targets but implicitly teaches models to suppress paralinguistic cues and acoustic events as noise. To address this, we propose Unified Audio Schema (UAS), a holistic and structured supervision framework that organizes audio information into three explicit components -- Transcription, Paralinguistics, and Non-linguistic Events -- within a unified JSON format. This design achieves comp...
| Authors | Linhao Zhang, Yuhan Song, Aiwei Liu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 14 April 2026 |
| Last updated at source | 14 April 2026 |
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