SOURCE-LINKED INTELLIGENCE
Where Does the Sound Go? Tracing Acoustic Information Loss in Audio-Conditioned LLMs
Audio-conditioned language models often underuse acoustic cues such as prosody, emotion, and non-speech sounds, raising the question of whether ASR-supervised frontends discard this information before it reaches the LM. We test whether the frontend is responsible by comparing Whisper-Tiny and Whisper-Small with EnCodec, DAC-VAE, and WavTokenizer in a shared Qwen3.5-4B audio-LM pipeline on ASR, emotion recognition, and sound captioning. Encoder replacement alone does not resolve this underuse: Whisper variants remain strongest overall, including on emotion and environmental sound captioning. To
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-05T04:24:16.000Z
First collected: 2026-09-20T21:32:07.623Z. This is not the publication date.