Papers › Clarinet: A Music Retrieval System

Clarinet: A Music Retrieval System

23 Oct 2022arXiv:2210.12648archive 2025-07-28

Kshitij Alwadhi, Rohan Sharma, Siddhant Sharma

A MIDI based approach for music recognition is proposed and implemented in this paper. Our Clarinet music retrieval system is designed to search piano MIDI files with high recall and speed. We design a novel melody extraction algorithm that improves recall results by more than 10%. We also implement 3 algorithms for retrieval-two self designed (RSA Note and RSA Time), and a modified version of the Mongeau Sankoff Algorithm. Algorithms to achieve tempo and scale invariance are also discussed in this paper. The paper also contains detailed experimentation and benchmarks with four different metrics. Clarinet achieves recall scores of more than 94%.

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Melody ExtractionRetrieval

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Methods

AttentionBridge-netClariNetConvolutionDV3 Attention BlockDV3 Convolution BlockDense ConnectionsDilated Causal ConvolutionDropoutGated Linear UnitL1 RegularizationMixture of Logistic DistributionsNormalizing FlowsReLUResidual ConnectionSoftmaxSoftsign ActivationWaveNetWeight Normalization

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