6 papers · 1 filter
Unfolded Recursive Expectation-Maximization Neural Network For Speaker Tracking
Rina Veler, Sharon Gannot
We propose a deep unfolded REM network for robust tracking of a single moving speaker in mild reverberant environments. Unlike classical REM algorithms, which rely on fixed-step-si…
Linearly Constrained Deep Beamformer for Multi-Speaker Scenarios
Ilai Zaidel, Ori Engel, Bar Engel +1
We propose a deep beamforming framework for enhancing target speaker(s) in multi-speaker environments. A deep neural network (DNN) is trained to estimate beamforming weights direct…
HRTF-guided Binaural Target Speaker Extraction with Real-World Validation
Yoav Ellinson, Sharon Gannot
This paper presents a Head-Related Transfer Function (HRTF)-guided framework for binaural Target Speaker Extraction (TSE) from mixtures of concurrent sources. Unlike conventional T…
Speakers Localization Using Batch EM In Unfolding Neural Network
Rina Veler, Sharon Gannot
We propose an interpretable Batch-EM Unfolded Network for robust speaker localization. By embedding the iterative EM procedure within an encoder-EM-decoder architecture, the method…
Interpretable Binaural Deep Beamforming Guided by Time-Varying Relative Transfer Function
Ilai Zaidel, Sharon Gannot
In this work, we propose a deep beamforming framework for speech enhancement in dynamic acoustic environments. The framework learns time-varying beamformer weights from noisy multi…
Binaural Target Speaker Extraction using Individualized HRTF
Yoav Ellinson, Sharon Gannot
In this work, we address the problem of binaural target-speaker extraction in the presence of multiple simultane-ous talkers. We propose a novel approach that leverages the individ…