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20152024
most citedSpeech Enhancement using a Deep Mixture of Experts

13 citations · 17 across the 9 of their papers we have counts for

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11 papers · 1 filter

eess.AS2024

Comparison of Frequency-Fusion Mechanisms for Binaural Direction-of-Arrival Estimation for Multiple Speakers

Daniel Fejgin, Elior Hadad, Sharon Gannot +2

To estimate the direction of arrival (DOA) of multiple speakers with methods that use prototype transfer functions, frequency-dependent spatial spectra (SPS) are usually constructe…

eess.AS2023

LipVoicer: Generating Speech from Silent Videos Guided by Lip Reading

Yochai Yemini, Aviv Shamsian, Lior Bracha +2

Lip-to-speech involves generating a natural-sounding speech synchronized with a soundless video of a person talking. Despite recent advances, current methods still cannot produce h…

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…

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…

eess.AS20204 cited

FCN Approach for Dynamically Locating Multiple Speakers

Hodaya Hammer, Shlomo E. Chazan, Jacob Goldberger +1

In this paper, we present a deep neural network-based online multi-speaker localisation algorithm. Following the W-disjoint orthogonality principle in the spectral domain, each tim…

eess.AS2020

Semi-supervised source localization with deep generative modeling

Michael J. Bianco, Sharon Gannot, Peter Gerstoft

We propose a semi-supervised localization approach based on deep generative modeling with variational autoencoders (VAEs). Localization in reverberant environments remains a challe…