activity
20152023
most citedSpeech Enhancement using a Deep Mixture of Experts

13 citations · 21 across the 11 of their papers we have counts for

collaborators

13 papers

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.CL2022

Don't Be So Sure! Boosting ASR Decoding via Confidence Relaxation

Tomer Wullach, Shlomo E. Chazan

Automatic Speech Recognition (ASR) systems frequently use a search-based decoding strategy aiming to find the best attainable transcript by considering multiple candidates. One pro…

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.CL2022

Enhancing Speech Recognition Decoding via Layer Aggregation

Tomer Wullach, Shlomo E. Chazan

Recently proposed speech recognition systems are designed to predict using representations generated by their top layers, employing greedy decoding which isolates each timestep fro…

cs.SD2022★ 4 cited

CNN self-attention voice activity detector

Amit Sofer, Shlomo E. Chazan

In this work we present a novel single-channel Voice Activity Detector (VAD) approach. We utilize a Convolutional Neural Network (CNN) which exploits the spatial information of the…

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…