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H2H Music Improv: A Communication Model and Audio-Visual Dataset for Music Improvisation — arXiv:2608.13957

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.13957
License (as archived): CC0-1.0
Archived: 2026-10-19T04:07:38.752Z
SHA-256 of the archived text: 8ad89104bb56017e7b84ddc3359b1d87b5487a1b665531a2378c08cdfd77e30f
Stable URL of this page: https://metraipolis.com/documento/dc_692ed8dbffef

How to cite

H2H Music Improv: A Communication Model and Audio-Visual Dataset for Music Improvisation — arXiv:2608.13957 — arXiv (en), https://arxiv.org/abs/2608.13957 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_692ed8dbffef (Metraipolis archive dc_692ed8dbffef, sha256 8ad89104bb56017e7b84ddc3359b1d87b5487a1b665531a2378c08cdfd77e30f)

BibTeX

@misc{dc692ed8dbffef,
  title = {H2H Music Improv: A Communication Model and Audio-Visual Dataset for Music Improvisation — arXiv:2608.13957},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.13957},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_692ed8dbffef; sha256 8ad89104bb56017e7b84ddc3359b1d87b5487a1b665531a2378c08cdfd77e30f},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.13957. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Current real-time AI improvisation systems lack the communication awareness human musicians rely on: rather than treating communication as a foundational algorithm design concern, most systems layer interaction strategies post-hoc onto generative algorithms through explicit controls and predefined modes. This gap persists in part because no formalized, machine-readable communication model with musicians exists. To address this, we study how expert musicians communicate in free (non-idiomatic) improvisation, unconstrained by prior discussion or agreement. Through a collaborative co-design process with expert improvisers, we derive a communication model that (1) captures how free improvisers negotiate musical ideas and enter stable musical spaces, and (2) is formalized as a machine-readable annotation scheme. We further present the H2H (Human-to-Human) Music Improvisation dataset: six hours of audio-visual expert duo improvisations with clean per-player stems and per-player annotations of both their own intentions and their perception of their partner's intentions. To our knowledge, this is the first such dataset for free improvisation. Together, the communication model and the dataset offer a new lens and resource for studying musician communication and may in future inform the design of AI musical partners that communicate by design.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-17 in cs.MM).
Categorie arXiv: Sound (cs.SD) ; Multimedia (cs.MM); Audio and Speech Processing (eess.AS).
Pagina del lavoro: https://arxiv.org/abs/2608.13957 — 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 2026-10-19T03:58:53.650Z dalla pagina https://arxiv.org/catchup/cs.MM/2026-08-17?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).