nmf_audio_benchmark: Benchmarking NMF algorithms on audio tasks - Equipe Better Representations for Artificial Intelligence
Conference Poster Year : 2024

nmf_audio_benchmark: Benchmarking NMF algorithms on audio tasks

Abstract

Introducing nmf_audio_benchmark (https://github.com/ax-le/nmf_audio_benchmark/), an open-source toolbox for benchmarking NMF algorithms and variants on audio tasks. This toolbox was designed because new low-rank factorization models are still being developed (in particular under new constraints or objective functions), but testing them under real conditions with audio data is not easy. In that spirit, this toolbox was primarily created to: - Provide a standardized framework for evaluating NMF-based audio processing techniques. - Offer a collection of audio datasets and pre-processing - Include a set of baseline NMF algorithms for comparison. - Enable easy integration of new NMF models for benchmarking. This toolbox is primarily designed for people developing new low-rank factorization models. Hence, it should be easy to add new NMF algorithms.
Fichier principal
Vignette du fichier
GdR_Poster__nmf_audio_benchmark.pdf (324.2 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04753826 , version 1 (25-10-2024)

Licence

Identifiers

  • HAL Id : hal-04753826 , version 1

Cite

Axel Marmoret. nmf_audio_benchmark: Benchmarking NMF algorithms on audio tasks. Journée "Synthèse en traitement du signal audionumérique", GDR IASIS, Nov 2024, Paris, France. ⟨hal-04753826⟩
0 View
0 Download

Share

More