activity
20152022
most citedSpeech Enhancement using a Deep Mixture of Experts

13 citations · 17 across the 8 of their papers we have counts for

collaborators

18 papers

cs.SD2022

Magnitude or Phase? A Two Stage Algorithm for Dereverberation

Ayal Schwartz, Sharon Gannot, Shlomo E. Chazan

In this work we present a new single-microphone speech dereverberation algorithm. First, a performance analysis is presented to interpret that algorithms focused on improving solel…

cs.SD2022

Single microphone speaker extraction using unified time-frequency Siamese-Unet

Aviad Eisenberg, Sharon Gannot, Shlomo E. Chazan

In this paper we present a unified time-frequency method for speaker extraction in clean and noisy conditions. Given a mixed signal, along with a reference signal, the common appro…

eess.AS2021

dEchorate: a Calibrated Room Impulse Response Database for Echo-aware Signal Processing

Diego Di Carlo, Pinchas Tandeitnik, Cédric Foy +3

This paper presents dEchorate: a new database of measured multichannel Room Impulse Responses (RIRs) including annotations of early echo timings and 3D positions of microphones, re…

cs.SD2021

Speech enhancement with mixture-of-deep-experts with clean clustering pre-training

Shlomo E. Chazan, Jacob Goldberger, Sharon Gannot

In this study we present a mixture of deep experts (MoDE) neural-network architecture for single microphone speech enhancement. Our architecture comprises a set of deep neural netw…

eess.SP2021

Semi-supervised source localization in reverberant environments with deep generative modeling

Michael J. Bianco, Sharon Gannot, Efren Fernandez-Grande +1

We propose a semi-supervised approach to acoustic source localization in reverberant environments based on deep generative modeling. Localization in reverberant environments remain…

eess.AS2020

Misalignment Recognition in Acoustic Sensor Networks using a Semi-supervised Source Estimation Method and Markov Random Fields

Gabriel F Miller, Andreas Brendel, Walter Kellermann +1

In this paper, we consider the problem of acoustic source localization by acoustic sensor networks (ASNs) using a promising, learning-based technique that adapts to the acoustic en…