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Ambisonics Encoding of Room Impulse Responses using a Device-Agnostic Diffusion Model — arXiv:2608.14097

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.14097
License (as archived): CC0-1.0
Archived: 2026-10-19T04:16:09.745Z
SHA-256 of the archived text: ec16591b666f28b0f897f8b0e4f66a6e92458d811be750122bc2571e47b787bb
Stable URL of this page: https://metraipolis.com/documento/dc_eac8aef8b185

How to cite

Ambisonics Encoding of Room Impulse Responses using a Device-Agnostic Diffusion Model — arXiv:2608.14097 — arXiv (en), https://arxiv.org/abs/2608.14097 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_eac8aef8b185 (Metraipolis archive dc_eac8aef8b185, sha256 ec16591b666f28b0f897f8b0e4f66a6e92458d811be750122bc2571e47b787bb)

BibTeX

@misc{dceac8aef8b185,
  title = {Ambisonics Encoding of Room Impulse Responses using a Device-Agnostic Diffusion Model — arXiv:2608.14097},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.14097},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_eac8aef8b185; sha256 ec16591b666f28b0f897f8b0e4f66a6e92458d811be750122bc2571e47b787bb},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.14097. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

We address the problem of encoding room impulse responses (RIRs) into high-order Ambisonics (HOA) representations from arbitrary and potentially insufficient or incomplete microphone array measurements. This task is fundamentally ill-posed for microphone arrays with limited spatial capture capabilities, such as irregular or sparse arrays, as classical linear methods fail to reconstruct high-order spatial detail. We introduce a diffusion-based generative framework that models the statistical properties of HOA RIRs. This enables device-agnostic encoding from arbitrary microphone arrays, potentially unseen during data measurement. Our approach incorporates a posterior sampling procedure that enforces consistency between the estimated signals and the measurements while plausibly reconstructing spatial information that is unobservable from the limited measurements alone. Experiments on simulated data demonstrate that our method outperforms linear and neural baselines, achieving accurate HOA RIR estimation up to 12th order. A listening test with binaural renderings, including both simulated and measured RIRs, further confirms that the proposed method yields higher perceptual similarity to reference Ambisonics RIRs than all baselines. The flexibility and accuracy of the proposed framework opens new possibilities for scalable acoustics simulations.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-17 in eess.AS).
Categorie arXiv: Audio and Speech Processing (eess.AS) ; Sound (cs.SD).
Pagina del lavoro: https://arxiv.org/abs/2608.14097 — 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 2026-10-19T04:12:15.703Z dalla pagina https://arxiv.org/catchup/eess.AS/2026-08-17?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).