A Lightweight Instrument-Agnostic Model for Polyphonic Note Transcription and Multipitch Estimation

research work·research paper·active

Research work examining evaluation benchmark, music transcription.

Recorded facts

Official site	https://arxiv.org/abs/2203.09893 ↗
Geography	Global
arxiv	2203.09893
venue	arXiv preprint
authors	Rachel M. Bittner; Juan José Bosch; David Rubinstein; Gabriel Meseguer-Brocal; Sebastian Ewert
methods	benchmark evaluation
code urls	unknown
demo urls	unknown
exact title	A Lightweight Instrument-Agnostic Model for Polyphonic Note Transcription and Multipitch Estimation
project urls	unknown
original title	unknown
citation counts	unknown
research topics	evaluation benchmark; music transcription
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	Spotify
publication or preprint date	2022-03-18
abstract level neutral summary	The work studies evaluation benchmark, music transcription; 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.