Clarinet: A Music Retrieval System
Kshitij Alwadhi, Rohan Sharma, Siddhant Sharma

TL;DR
This paper introduces Clarinet, a MIDI-based music retrieval system that employs novel melody extraction and retrieval algorithms, achieving high recall and speed for piano MIDI file searches.
Contribution
The paper presents a new melody extraction algorithm and three retrieval algorithms, including two self-designed and one modified, enhancing music retrieval accuracy and efficiency.
Findings
Melody extraction improves recall by over 10%
Clarinet achieves over 94% recall score
System demonstrates high speed and accuracy in music retrieval
Abstract
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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Taxonomy
TopicsMusic and Audio Processing · Music Technology and Sound Studies · Speech and Audio Processing
MethodsGated Linear Unit · HuMan(Expedia)||How do I get a human at Expedia? · Attention Is All You Need · Dilated Causal Convolution · Softmax · Convolution · Residual Connection · Dropout · *Communicated@Fast*How Do I Communicate to Expedia? · Mixture of Logistic Distributions
