10 papers
Phase retrieval with Bregman divergences: Application to audio signal recovery
Pierre-Hugo Vial, Paul Magron, Thomas Oberlin +1
Phase retrieval aims to recover a signal from magnitude or power spectra measurements. It is often addressed by considering a minimization problem involving a quadratic cost functi…
Leveraging the structure of musical preference in content-aware music recommendation
Paul Magron, Cédric Févotte
State-of-the-art music recommendation systems are based on collaborative filtering, which predicts a user's interest from his listening habits and similarities with other users' pr…
Phase recovery with Bregman divergences for audio source separation
Paul Magron, Pierre-Hugo Vial, Thomas Oberlin +1
Time-frequency audio source separation is usually achieved by estimating the short-time Fourier transform (STFT) magnitude of each source, and then applying a phase recovery algori…
Phase retrieval with Bregman divergences and application to audio signal recovery
Pierre-Hugo Vial, Paul Magron, Thomas Oberlin +1
Phase retrieval (PR) aims to recover a signal from the magnitudes of a set of inner products. This problem arises in many audio signal processing applications which operate on a sh…
Online Spectrogram Inversion for Low-Latency Audio Source Separation
Paul Magron, Tuomas Virtanen
Audio source separation is usually achieved by estimating the short-time Fourier transform (STFT) magnitude of each source, and then applying a spectrogram inversion algorithm to r…
Language Modelling for Sound Event Detection with Teacher Forcing and Scheduled Sampling
Konstantinos Drossos, Shayan Gharib, Paul Magron +1
A sound event detection (SED) method typically takes as an input a sequence of audio frames and predicts the activities of sound events in each frame. In real-life recordings, the…