SingSong: Generating musical accompaniments from singing
research work·research paper·active
Research work examining audio generation, automatic accompaniment.
Verified facts
| Official site | https://arxiv.org/abs/2301.12662 ↗ |
|---|---|
| Geography | Global |
| arxiv | 2301.12662 |
| venue | arXiv preprint |
| authors | Chris Donahue; Antoine Caillon; Adam Roberts; Ethan Manilow; Philippe Esling; Andrea Agostinelli; Mauro Verzetti; Ian Simon; Olivier Pietquin; Neil Zeghidour; Jesse Engel |
| methods | retrieval |
| code urls | unknown |
| demo urls | unknown |
| exact title | SingSong: Generating musical accompaniments from singing |
| project urls | https://g.co/magenta/singsong |
| original title | unknown |
| citation counts | unknown |
| research topics | audio generation; automatic accompaniment; music retrieval; singing voice |
| peer review status | not established from abstract metadata |
| disclosed conflicts | unknown |
| stated contribution | Presents or evaluates the system, method, benchmark, or analysis identified in the paper title. |
| us market scope basis | Included as a materially relevant public research artifact in the US-facing AI-music ecosystem; direct affiliation varies. |
| funding acknowledgements | unknown |
| affiliations at publication | Google Research |
| publication or preprint date | 2023-01-30 |
| abstract level neutral summary | The work studies audio generation, automatic accompaniment; methods and evaluation details are in the official abstract. |
| datasets benchmarks models tools used | unknown |
| correction withdrawal retraction status | No withdrawal marker observed in captured arXiv metadata. |
Current
| affiliated with | Google Research 2023-01-30 — now |
|---|
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