11 papers · 1 filter
A Phoneme-Scale Assessment of Multichannel Speech Enhancement Algorithms
Nasser-Eddine Monir, Paul Magron, Romain Serizel
In the intricate acoustic landscapes where speech intelligibility is challenged by noise and reverberation, multichannel speech enhancement emerges as a promising solution for indi…
Spectrogram Inversion for Audio Source Separation via Consistency, Mixing, and Magnitude Constraints
Paul Magron, Tuomas Virtanen
Audio source separation is often achieved by estimating the magnitude spectrogram of each source, and then applying a phase recovery (or spectrogram inversion) algorithm to retriev…
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…
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…