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20172022
most citedLibriMix: An Open-Source Dataset for Generalizable Speech Separation

183 citations · 507 across the 18 of their papers we have counts for

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Showing 2020Show all

7 papers · 1 filter

eess.AS20201 cited

UIAI System for Short-Duration Speaker Verification Challenge 2020

Md Sahidullah, Achintya Kumar Sarkar, Ville Vestman +5

In this work, we present the system description of the UIAI entry for the short-duration speaker verification (SdSV) challenge 2020. Our focus is on Task 1 dedicated to text-depend…

eess.AS2020183 cited

LibriMix: An Open-Source Dataset for Generalizable Speech Separation

Joris Cosentino, Manuel Pariente, Samuele Cornell +2

In recent years, wsj0-2mix has become the reference dataset for single-channel speech separation. Most deep learning-based speech separation models today are benchmarked on it. How…

eess.AS20202 cited

Design Choices for X-vector Based Speaker Anonymization

Brij Mohan Lal Srivastava, Natalia Tomashenko, Xin Wang +5

The recently proposed x-vector based anonymization scheme converts any input voice into that of a random pseudo-speaker. In this paper, we present a flexible pseudo-speaker selecti…

eess.AS202051 cited

Asteroid: the PyTorch-based audio source separation toolkit for researchers

Manuel Pariente, Samuele Cornell, Joris Cosentino +11

This paper describes Asteroid, the PyTorch-based audio source separation toolkit for researchers. Inspired by the most successful neural source separation systems, it provides all…

cs.SD202097 cited

CHiME-6 Challenge:Tackling Multispeaker Speech Recognition for Unsegmented Recordings

Shinji Watanabe, Michael Mandel, Jon Barker +18

Following the success of the 1st, 2nd, 3rd, 4th and 5th CHiME challenges we organize the 6th CHiME Speech Separation and Recognition Challenge (CHiME-6). The new challenge revisits…

eess.AS2020

Foreground-Background Ambient Sound Scene Separation

Michel Olvera, Emmanuel Vincent, Romain Serizel +1

Ambient sound scenes typically comprise multiple short events occurring on top of a somewhat stationary background. We consider the task of separating these events from the backgro…