Philippe Esling

Streamable Neural Audio Synthesis With Non-Causal Convolutions

Apr 14, 2022
Antoine Caillon , Philippe Esling

Figure 2 for Streamable Neural Audio Synthesis With Non-Causal Convolutions

Figure 3 for Streamable Neural Audio Synthesis With Non-Causal Convolutions

Figure 4 for Streamable Neural Audio Synthesis With Non-Causal Convolutions

HEAR 2021: Holistic Evaluation of Audio Representations

Mar 26, 2022
Joseph Turian , Jordie Shier , Humair Raj Khan , Bhiksha Raj , Björn W. Schuller , Christian J. Steinmetz , Colin Malloy , George Tzanetakis , Gissel Velarde , Kirk McNally , Max Henry , Nicolas Pinto , Camille Noufi , Christian Clough , Dorien Herremans , Eduardo Fonseca , Jesse Engel , Justin Salamon , Philippe Esling , Pranay Manocha , Shinji Watanabe , Zeyu Jin , Yonatan Bisk

Figure 2 for HEAR 2021: Holistic Evaluation of Audio Representations

Figure 3 for HEAR 2021: Holistic Evaluation of Audio Representations

Figure 4 for HEAR 2021: Holistic Evaluation of Audio Representations

* to appear in Proceedings of Machine Learning Research (PMLR): NeurIPS 2021 Competition Track

Access Paper or Ask Questions

RAVE: A variational autoencoder for fast and high-quality neural audio synthesis

Nov 09, 2021
Antoine Caillon , Philippe Esling

Figure 2 for RAVE: A variational autoencoder for fast and high-quality neural audio synthesis

Figure 3 for RAVE: A variational autoencoder for fast and high-quality neural audio synthesis

Figure 4 for RAVE: A variational autoencoder for fast and high-quality neural audio synthesis

Access Paper or Ask Questions

Signal-domain representation of symbolic music for learning embedding spaces

Sep 08, 2021
Mathieu Prang , Philippe Esling

Figure 2 for Signal-domain representation of symbolic music for learning embedding spaces

Figure 3 for Signal-domain representation of symbolic music for learning embedding spaces

Figure 4 for Signal-domain representation of symbolic music for learning embedding spaces

* The 2020 Joint Conference on AI Music Creativity, Oct 2020, Stockholm, Sweden

Access Paper or Ask Questions

A Multi-Objective Approach for Sustainable Generative Audio Models

Jul 06, 2021
Constance Douwes , Philippe Esling , Jean-Pierre Briot

Figure 2 for A Multi-Objective Approach for Sustainable Generative Audio Models

Figure 3 for A Multi-Objective Approach for Sustainable Generative Audio Models

Figure 4 for A Multi-Objective Approach for Sustainable Generative Audio Models

* 9 pages, 3 figures

Access Paper or Ask Questions

Spectrogram Inpainting for Interactive Generation of Instrument Sounds

Apr 15, 2021
Théis Bazin , Gaëtan Hadjeres , Philippe Esling , Mikhail Malt

Figure 2 for Spectrogram Inpainting for Interactive Generation of Instrument Sounds

Figure 3 for Spectrogram Inpainting for Interactive Generation of Instrument Sounds

Figure 4 for Spectrogram Inpainting for Interactive Generation of Instrument Sounds

* Proceedings of the 1st Joint Conference on AI Music Creativity, 2020 (p. 10). Stockholm, Sweden: AIMC
* 8 pages + references + appendices. 4 figures. Published as a conference paper at the The 2020 Joint Conference on AI Music Creativity, October 19-23, 2020, organized and hosted virtually by the Royal Institute of Technology (KTH), Stockholm, Sweden

Access Paper or Ask Questions