36 citations · 223 across the 30 of their papers we have counts for
7 papers · 1 filter
Timbre latent space: exploration and creative aspects
Antoine Caillon, Adrien Bitton, Brice Gatinet +1
Recent studies show the ability of unsupervised models to learn invertible audio representations using Auto-Encoders. They enable high-quality sound synthesis but a limited control…
Creativity in the era of artificial intelligence
Philippe Esling, Ninon Devis
Creativity is a deeply debated topic, as this concept is arguably quintessential to our humanity. Across different epochs, it has been infused with an extensive variety of meanings…
Neural Granular Sound Synthesis
Adrien Bitton, Philippe Esling, Tatsuya Harada
Granular sound synthesis is a popular audio generation technique based on rearranging sequences of small waveform windows. In order to control the synthesis, all grains in a given…
Ultra-light deep MIR by trimming lottery tickets
Philippe Esling, Theis Bazin, Adrien Bitton +2
Current state-of-the-art results in Music Information Retrieval are largely dominated by deep learning approaches. These provide unprecedented accuracy across all tasks. However, t…
Diet deep generative audio models with structured lottery
Philippe Esling, Ninon Devis, Adrien Bitton +3
Deep learning models have provided extremely successful solutions in most audio application fields. However, the high accuracy of these models comes at the expense of a tremendous…
Vector-Quantized Timbre Representation
Adrien Bitton, Philippe Esling, Tatsuya Harada
Timbre is a set of perceptual attributes that identifies different types of sound sources. Although its definition is usually elusive, it can be seen from a signal processing viewp…