2 papers
cs.SD2026
Predicting Timbre Traits for Interpretable Assessment of Musical Sound Synthesizers
Théo Chasle Cauchy, Modan Tailleur, Lindsey Reymore +2
Measuring neural audio synthesizers' performance is now routinely conducted using distribution based metrics such as the Fréchet Audio Distance (FAD). Although this metric can be c…
eess.AS2018
Autoencoders for music sound modeling: a comparison of linear, shallow, deep, recurrent and variational models
Fanny Roche, Thomas Hueber, Samuel Limier +1
This study investigates the use of non-linear unsupervised dimensionality reduction techniques to compress a music dataset into a low-dimensional representation which can be used i…