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AudioWorldSim: Realistic Binaural Audio Datasets For World Models — arXiv:2608.21075

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.21075
License (as archived): CC0-1.0
Archived: 2026-10-18T10:31:31.279Z
SHA-256 of the archived text: de7f30a890e2d0bd349392ba4a98e916b1c0cea6b480795643e8ea29ecc75641
Stable URL of this page: https://metraipolis.com/documento/dc_cfcf0bc0168b

How to cite

AudioWorldSim: Realistic Binaural Audio Datasets For World Models — arXiv:2608.21075 — arXiv (en), https://arxiv.org/abs/2608.21075 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_cfcf0bc0168b (Metraipolis archive dc_cfcf0bc0168b, sha256 de7f30a890e2d0bd349392ba4a98e916b1c0cea6b480795643e8ea29ecc75641)

BibTeX

@misc{dccfcf0bc0168b,
  title = {AudioWorldSim: Realistic Binaural Audio Datasets For World Models — arXiv:2608.21075},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.21075},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_cfcf0bc0168b; sha256 de7f30a890e2d0bd349392ba4a98e916b1c0cea6b480795643e8ea29ecc75641},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.21075. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

This technical report presents AudioWorldSim, an open-source platform designed to generate realistic binaural audio datasets and advance research in audio-based machine learning, particularly world models. Built as a custom extension of Meta's SoundSpaces 2.0 platform, AudioWorldSim leverages their comprehensive acoustics framework, but focuses on the automatic rollout of random agent navigations, as well as implements crucial fixes to how continuous sound is composed. AudioWorldSim is made publicly available to the research community at this https URL to facilitate reproducibility.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-24 in cs.LG).
Categorie arXiv: Sound (cs.SD) ; Machine Learning (cs.LG).
Pagina del lavoro: https://arxiv.org/abs/2608.21075 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-18T10:27:56.001Z dalla pagina https://arxiv.org/catchup/cs.LG/2026-08-24?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).