CARES: A Controlled Synthetic Benchmark of Speaker Reactions to Sound
Automatic audio scene description turns a recording into a text account of a situation. One difficulty is deciding which elements of the audio should be kept, since a description cannot include them all. Annotators disagree about this, making a ground truth hard to obtain. In this work, we first define the ground truth, then generate the data. We focus on audio events and define sound salience with a simple rule: a sound is salient when a speaker audibly reacts to it. For scale and variety, a controlled set of scenarios fixes the ground truth, and a language model writes the dialogues. The resulting corpus, CARES, contains 10,000 two-speaker scenes. We then benchmark six audio-language mo...
| Authors | Marcel Gibier, Thomas Thebaud, Olivier Boëffard et al. |
|---|---|
| Primary category | cs.SD |
| Published | 7 October 2026 |
| Last updated at source | 7 October 2026 |
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