S
Sunit Sivasankaran
Researcher at University of Lorraine
Publications - 21
Citations - 355
Sunit Sivasankaran is an academic researcher from University of Lorraine. The author has contributed to research in topics: Word error rate & Speech enhancement. The author has an hindex of 9, co-authored 19 publications receiving 240 citations. Previous affiliations of Sunit Sivasankaran include Indian Institute of Technology Madras & French Institute for Research in Computer Science and Automation.
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Proceedings ArticleDOI
Asteroid: The PyTorch-Based Audio Source Separation Toolkit for Researchers.
Manuel Pariente,Samuele Cornell,Joris Cosentino,Sunit Sivasankaran,Efthymios Tzinis,Jens Heitkaemper,Michel Olvera,Fabian-Robert Stöter,Mathieu Hu,Juan M. Martín-Doñas,David Ditter,Ariel Frank,Antoine Deleforge,Emmanuel Vincent +13 more
TL;DR: In this paper, the PyTorch-based audio source separation toolkit Asteroid is described, inspired by the most successful neural source separation systems, it provides all neu-ral building blocks required to build such a system.
Proceedings ArticleDOI
Robust ASR using neural network based speech enhancement and feature simulation
Sunit Sivasankaran,Aditya Arie Nugraha,Emmanuel Vincent,Juan A. Morales-Cordovilla,Siddharth Dalmia,Irina Illina,Antoine Liutkus +6 more
TL;DR: A deep neural network based multichannel speech enhancement technique, where the speech and noise spectra are estimated using a DNN based regressor and the spatial parameters are derived in an expectation-maximization (EM) like fashion.
Proceedings ArticleDOI
Keyword Based Speaker Localization: Localizing a Target Speaker in a Multi-speaker Environment.
TL;DR: This work introduces the new task of localizing the speaker who uttered a given keyword, e.g., the wake-up word of a distant-microphone voice command system, in the presence of overlapping speech.
Proceedings ArticleDOI
A French corpus for distant-microphone speech processing in real homes
Nancy Bertin,Ewen Camberlein,Emmanuel Vincent,Romain Lebarbenchon,Stéphane Peillon,Éric Lamandé,Sunit Sivasankaran,Frédéric Bimbot,Irina Illina,Ariane Tom,Sylvain Fleury,Eric Jamet +11 more
TL;DR: A new corpus for distant- microphone speech processing in domestic environments that includes reverberated, noisy speech signals spoken by native French talkers in a lounge and recorded by an 8-microphone device at various angles and distances and in various noise conditions is introduced.
Proceedings ArticleDOI
Phone Merging For Code-Switched Speech Recognition
TL;DR: Evidence that phone sharing between languages improves the Acoustic Model performance for Hindi-English code-switched speech is shown and multiple data-driven methods to identify phones to be merged across the languages are investigated.