Optimal spectral transportation with application to music transcription
Authors: Rémi Flamary, Cédric Févotte, Nicolas Courty, Valentin Emiya
NeurIPS 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | A very fast and simple decomposition algorithm that achieves state-of-the-art performance on real musical data. and 6 Experiments |
| Researcher Affiliation | Academia | Rémi Flamary Université Côte d Azur, CNRS, OCA remi.flamary@unice.fr Cédric Févotte CNRS, IRIT, Toulouse cedric.fevotte@irit.fr Nicolas Courty Université de Bretagne Sud, CNRS, IRISA courty@univ-ubs.fr Valentin Emiya Aix-Marseille Université, CNRS, LIF valentin.emiya@lif.univ-mrs.fr |
| Pseudocode | No | The paper describes the proposed algorithm steps in prose but does not provide structured pseudocode or an algorithm block. |
| Open Source Code | Yes | A Python implementation of OST and real-time demonstrator are available at https://github. com/rflamary/OST |
| Open Datasets | Yes | We consider in this section the transcription of a selection of real piano recordings, obtained from the MAPS dataset (Emiya et al., 2010). |
| Dataset Splits | Yes | Half of the recording is used for validation of the hyper-parameters and the other half is used as test data. |
| Hardware Specification | No | The paper mentions results were run 'on an average desktop PC' but does not provide specific hardware details such as CPU/GPU models or memory. |
| Software Dependencies | No | The paper does not provide specific version numbers for any software dependencies. |
| Experiment Setup | Yes | For PLCA, we validated 4 and 3 values of the width and amplitude dampening of the Gaussian kernels used to synthesise the dictionary. For OST, we set ϵ = qϵ0 in Eq. (4), which was found to satisfactorily improve the discrimination of octaves increasingly with frequency, and validated 5 orders of magnitude of ϵ0. For OSTe, we additionally validated 4 orders of magnitude of λe. |