Search Results for author: Anis Khlif

Found 3 papers, 2 papers with code

Spleeter: A Fast And State-of-the Art Music Source Separation Tool With Pre-trained Models

3 code implementations ISMIR 2019 Late-Breaking/Demo 2019 Romain Hennequin, Anis Khlif, Felix Voituret, Manuel Moussallam

We present and release a new tool for music source separation with pre-trained models called Spleeter. Spleeter was designed with ease of use, separation performance and speed in mind.

Ranked #19 on Music Source Separation on MUSDB18 (using extra training data)

Music Source Separation Speech Enhancement

Leveraging Knowledge Bases And Parallel Annotations For Music Genre Translation

2 code implementations18 Jul 2019 Elena V. Epure, Anis Khlif, Romain Hennequin

Here, we choose a new angle for the genre study by seeking to predict what would be the genres of musical items in a target tag system, knowing the genres assigned to them within source tag systems.

Diversity regression +2

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