10 papers
Harmonic-Percussive Disentangled Neural Audio Codec for Bandwidth Extension
Benoît Giniès, Xiaoyu Bie, Olivier Fercoq +1
Bandwidth extension, the task of reconstructing the high-frequency components of an audio signal from its low-pass counterpart, is a long-standing problem in audio processing. Whil…
Is Phase Really Needed for Weakly-Supervised Dereverberation ?
Marius Rodrigues, Louis Bahrman, Roland Badeau +1
In unsupervised or weakly-supervised approaches for speech dereverberation, the target clean (dry) signals are considered to be unknown during training. In that context, evaluating…
PESTO: Real-Time Pitch Estimation with Self-supervised Transposition-equivariant Objective
Alain Riou, Bernardo Torres, Ben Hayes +4
In this paper, we introduce PESTO, a self-supervised learning approach for single-pitch estimation using a Siamese architecture. Our model processes individual frames of a Variable…
Soft Disentanglement in Frequency Bands for Neural Audio Codecs
Benoit Ginies, Xiaoyu Bie, Olivier Fercoq +1
In neural-based audio feature extraction, ensuring that representations capture disentangled information is crucial for model interpretability. However, existing disentanglement me…
The Inverse Drum Machine: Source Separation Through Joint Transcription and Analysis-by-Synthesis
Bernardo Torres, Geoffroy Peeters, Gael Richard
We present the Inverse Drum Machine, a novel approach to Drum Source Separation that leverages an analysis-by-synthesis framework combined with deep learning. Unlike recent supervi…
Translation-Equivariant Self-Supervised Learning for Pitch Estimation with Optimal Transport
Bernardo Torres, Alain Riou, Gaël Richard +1
In this paper, we propose an Optimal Transport objective for learning one-dimensional translation-equivariant systems and demonstrate its applicability to single pitch estimation.…