activity
20242026
most citedMulti-Microphone and Multi-Modal Emotion Recognition in Reverberant Environment

2 citations · 5 across the 9 of their papers we have counts for

collaborators

10 papers

eess.AS2026

Voice Agents under Acoustic Stress: From Signal Degradation to Interaction and Action

Amir Ivry, Kai-Wei Chang, Lin Zhang +2

Voice agents must complete users' tasks despite noise, reverberation, and competing speech. Evaluating agents' robustness therefore requires following how acoustic conditions affec…

eess.AS2026

AMDM-SE: Attention-based Multichannel Diffusion Model for Speech Enhancement

Renana Opochinsky, Sharon Gannot

Diffusion models have recently achieved impressive results in reconstructing images from noisy inputs, and similar ideas have been applied to speech enhancement by treating time-fr…

eess.AS2025

Transient Noise Removal via Diffusion-based Speech Inpainting

Mordehay Moradi, Sharon Gannot

In this paper, we present PGDI, a diffusion-based speech inpainting framework for restoring missing or severely corrupted speech segments. Unlike previous methods that struggle wit…

cs.SD2024★ 2 cited

Multi-Microphone and Multi-Modal Emotion Recognition in Reverberant Environment

Ohad Cohen, Gershon Hazan, Sharon Gannot

This paper presents a Multi-modal Emotion Recognition (MER) system designed to enhance emotion recognition accuracy in challenging acoustic conditions. Our approach combines a modi…

eess.AS2024

Audio-Visual Approach For Multimodal Concurrent Speaker Detection

Amit Eliav, Sharon Gannot

Concurrent Speaker Detection (CSD), the task of identifying active speakers and their overlaps in an audio signal, is essential for various audio applications, including meeting tr…

eess.AS2024

Multi-Microphone Speech Emotion Recognition using the Hierarchical Token-semantic Audio Transformer Architecture

Ohad Cohen, Gershon Hazan, Sharon Gannot

The performance of most emotion recognition systems degrades in real-life situations ('in the wild' scenarios) where the audio is contaminated by reverberation. Our study explores…

eess.AS2024

SingIt! Singer Voice Transformation

Amit Eliav, Aaron Taub, Renana Opochinsky +1

In this paper, we propose a model which can generate a singing voice from normal speech utterance by harnessing zero-shot, many-to-many style transfer learning. Our goal is to give…

cs.RO2024★ 2 cited

Socially Pertinent Robots in Gerontological Healthcare

Xavier Alameda-Pineda, Angus Addlesee, Daniel Hernández García +41

Despite the many recent achievements in developing and deploying social robotics, there are still many underexplored environments and applications for which systematic evaluation o…

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.AS2024★ 1 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…