SOTAVerified

Cover song identification

Cover Song Identification is the task of identifying an alternative version of a previous musical piece, even though it may differ substantially in timbre, tempo, structure, and even fundamental aspects relating to the harmony and melody of the song. The term “cover” is so wide that it ranges from acoustic renditions of a previous song, to Jimi Hendrix’ famous (and radical) reinterpretation of Bob Dylan’s “All Along the Watchtower”, to Rage Against the Machine essentially rewriting Bob Dylan’s “Maggie’s Farm”. Beyond its value for computational musicology and for enhancing music recommendation, Cover Song Identification is of interest because of its potential for benchmarking other music similarity and retrieval algorithms. Chord analysis, melody extraction and music similarity are all strongly connected to Cover Song Identification - another field of music analysis where AI has been applied.

Source: Artificial Musical Intelligence: A Survey

Papers

Showing 110 of 18 papers

TitleStatusHype
On the Robustness of Cover Version Identification Models: A Study Using Cover Versions from YouTube0
Leveraging User-Generated Metadata of Online Videos for Cover Song Identification0
A Semi-Supervised Deep Learning Approach to Dataset Collection for Query-By-Humming TaskCode1
DisCover: Disentangled Music Representation Learning for Cover Song Identification0
CoverHunter: Cover Song Identification with Refined Attention and AlignmentsCode1
ByteCover3: Accurate Cover Song Identification on Short Queries0
WideResNet with Joint Representation Learning and Data Augmentation for Cover Song Identification0
BYTECOVER2: TOWARDS DIMENSIONALITY REDUCTION OF LATENT EMBEDDING FOR EFFICIENT COVER SONG IDENTIFICATION0
Contrastive Learning with Positive-Negative Frame Mask for Music Representation0
ByteCover: Cover Song Identification via Multi-Loss TrainingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SCNN-MMAP0.96Unverified
2ByteCoverMAP0.96Unverified
3CQT-NetMAP0.92Unverified
4MOVEMAP0.89Unverified