activity
20162024
most citedSemi-Supervised Source Localization on Multiple-Manifolds with Distributed Microphones

2 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

eess.AS2024

Explainable DNN-based Beamformer with Postfilter

Adi Cohen, Daniel Wong, Jung-Suk Lee +1

This paper introduces an explainable DNN-based beamformer with a postfilter (ExNet-BF+PF) for multichannel signal processing. Our approach combines the U-Net network with a beamfor…

eess.AS2024

RevRIR: Joint Reverberant Speech and Room Impulse Response Embedding using Contrastive Learning with Application to Room Shape Classification

Jacob Bitterman, Daniel Levi, Hilel Hagai Diamandi +2

This paper focuses on room fingerprinting, a task involving the analysis of an audio recording to determine the specific volume and shape of the room in which it was captured. Whil…

eess.AS2024

Concurrent Speaker Detection: A multi-microphone Transformer-Based Approach

Amit Eliav, Sharon Gannot

We present a deep-learning approach for the task of Concurrent Speaker Detection (CSD) using a modified transformer model. Our model is designed to handle multi-microphone data but…

eess.AS20241 cited

Single-Microphone Speaker Separation and Voice Activity Detection in Noisy and Reverberant Environments

Renana Opochinsky, Mordehay Moradi, Sharon Gannot

Speech separation involves extracting an individual speaker's voice from a multi-speaker audio signal. The increasing complexity of real-world environments, where multiple speakers…

cs.SD2023

A two-stage speaker extraction algorithm under adverse acoustic conditions using a single-microphone

Aviad Eisenberg, Sharon Gannot, Shlomo E. Chazan

In this work, we present a two-stage method for speaker extraction under reverberant and noisy conditions. Given a reference signal of the desired speaker, the clean, but the still…

cs.SD20162 cited

Semi-Supervised Source Localization on Multiple-Manifolds with Distributed Microphones

Bracha Laufer-Goldshtein, Ronen Talmon, Sharon Gannot

The problem of source localization with ad hoc microphone networks in noisy and reverberant enclosures, given a training set of prerecorded measurements, is addressed in this paper…