Paper year
2024
Paper dossier
The Sound Demixing Challenge 2023 - Music Demixing Track
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Citations
23
Authors
27
Topic labels
3
Source readout
Source and corpus status
Venue
Transactions of the International Society for Music Information Retrieval
Source slug
tismir
Corpus placement
Core corpus
Similarity rows
6
Ranking readout
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Run shadow-generalization-product-candidate-ranking-v1Top 50 surfaced
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Top 50
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Run label
shadow-generalization-product-candidate-ranking-v1
Snapshot
source-snapshot-shadow-generalization-v1-20260521
Scope: family global | run rank-83787b91ef
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Abstract
This paper summarizes the music demixing (MDX) track of the Sound Demixing Challenge (SDX'23). We provide a summary of the challenge setup and introduce the task of robust music source separation (MSS), i.e., training MSS models in the presence of errors in the training data. We propose a formalization of the errors that can occur in the design of a training dataset for MSS systems and introduce two new datasets that simulate such errors: SDXDB23_LabelNoise and SDXDB23_Bleeding.1 We describe the methods that achieved the highest scores in the competition. Moreover, we present a direct comparison with the previous edition of the challenge (the Music Demixing Challenge 2021): the best performing system achieved an improvement of over 1.6dB in signal-to-distortion ratio over the winner of the previous competition, when evaluated on MDXDB21. Besides relying on the signal-to-distortion ratio as objective metric, we also performed a listening test with renowned producers and musicians to study the perceptual quality of the systems and report here the results. Finally, we provide our insights into the organization of the competition and our prospects for future editions.
Authors
Neighborhood labels
Topics
3 labels
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Music and Audio ProcessingSpeech and Audio ProcessingMusic Technology and Sound Studies
Neighbor surface
Similar papers
6 total neighborsEmbedding v1-title-abstract-1536-cleantext-r3
Similar papers use a separately configured neighbor embedding; it may differ from the embedding version used by the current ranked run.
- Speech and Audio ProcessingMusic and Audio ProcessingBlind Source Separation Techniques
- Music and Audio ProcessingMusic Technology and Sound StudiesSpeech and Audio Processing
- Music and Audio ProcessingMusic Technology and Sound StudiesSpeech and Audio Processing
- Music and Audio ProcessingMusic Technology and Sound StudiesNeuroscience and Music Perception
- Music and Audio ProcessingMusic Technology and Sound StudiesSpeech and Audio Processing
- Music and Audio ProcessingEmotion and Mood RecognitionMusic Technology and Sound Studies
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