MuLan: A Joint Embedding of Music Audio and Natural Language

research work·research paper·active

Research work examining music retrieval, music/audio representation learning.

Recorded facts

Official site	https://arxiv.org/abs/2208.12415 ↗
Geography	Global
arxiv	2208.12415
venue	To appear in ISMIR 2022
authors	Qingqing Huang; Aren Jansen; Joonseok Lee; Ravi Ganti; Judith Yue Li; Daniel P. W. Ellis
methods	retrieval
code urls	unknown
demo urls	unknown
exact title	MuLan: A Joint Embedding of Music Audio and Natural Language
project urls	unknown
original title	unknown
citation counts	unknown
research topics	music retrieval; music/audio representation learning; music/audio understanding
peer review status	venue or acceptance claim recorded in arXiv comment
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	2022-08-26
abstract level neutral summary	The work studies music retrieval, music/audio representation learning; 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.