HSLU-AAI/DEAR

DEAR Dataset Dataset Summary The Deep Evaluation of Audio Representations (DEAR) dataset is a benchmark designed to assess general-purpose audio foundation models on properties critical for hearable devices. It comprises 1,158 mono audio tracks (30 s each), spatially mixing proprietary anechoic speech monologues with high-quality everyday acoustic scene recordings from the HOA‑SSR library. DEAR enables controlled evaluation of: Context (environment type:… See the full description on the dataset page: https://huggingface.co/datasets/HSLU-AAI/DEAR.