Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Titeux, Hadrien"'
Autor:
Lavechin, Marvin, Sy, Yaya, Titeux, Hadrien, Blandón, María Andrea Cruz, Räsänen, Okko, Bredin, Hervé, Dupoux, Emmanuel, Cristia, Alejandrina
Self-supervised techniques for learning speech representations have been shown to develop linguistic competence from exposure to speech without the need for human labels. In order to fully realize the potential of these approaches and further our und
Externí odkaz:
http://arxiv.org/abs/2306.01506
Autor:
de Seyssel, Maureen, Lavechin, Marvin, Titeux, Hadrien, Thomas, Arthur, Virlet, Gwendal, Revilla, Andrea Santos, Wisniewski, Guillaume, Ludusan, Bogdan, Dupoux, Emmanuel
We present ProsAudit, a benchmark in English to assess structural prosodic knowledge in self-supervised learning (SSL) speech models. It consists of two subtasks, their corresponding metrics, and an evaluation dataset. In the protosyntax task, the mo
Externí odkaz:
http://arxiv.org/abs/2302.12057
Autor:
Lavechin, Marvin, Métais, Marianne, Titeux, Hadrien, Boissonnet, Alodie, Copet, Jade, Rivière, Morgane, Bergelson, Elika, Cristia, Alejandrina, Dupoux, Emmanuel, Bredin, Hervé
Most automatic speech processing systems register degraded performance when applied to noisy or reverberant speech. But how can one tell whether speech is noisy or reverberant? We propose Brouhaha, a neural network jointly trained to extract speech/n
Externí odkaz:
http://arxiv.org/abs/2210.13248
Autor:
Riad, Rachid, Titeux, Hadrien, Lemoine, Laurie, Montillot, Justine, Sliwinski, Agnes, Bagnou, Jennifer Hamet, Cao, Xuan Nga, Bachoud-Lévi, Anne-Catherine, Dupoux, Emmanuel
Conversations between a clinician and a patient, in natural conditions, are valuable sources of information for medical follow-up. The automatic analysis of these dialogues could help extract new language markers and speed-up the clinicians' reports.
Externí odkaz:
http://arxiv.org/abs/2010.16131
Autor:
Riad, Rachid, Titeux, Hadrien, Lemoine, Laurie, Montillot, Justine, Bagnou, Jennifer Hamet, Cao, Xuan Nga, Dupoux, Emmanuel, Bachoud-Lévi, Anne-Catherine
Disease-modifying treatments are currently assessed in neurodegenerative diseases. Huntington's Disease represents a unique opportunity to design automatic sub-clinical markers, even in premanifest gene carriers. We investigated phonatory impairments
Externí odkaz:
http://arxiv.org/abs/2006.05365
Autor:
Titeux, Hadrien, Riad, Rachid, Cao, Xuan-Nga, Hamilakis, Nicolas, Madden, Kris, Cristia, Alejandrina, Bachoud-Lévi, Anne-Catherine, Dupoux, Emmanuel
Publikováno v:
LREC 2020 - 12th Language Resources and Evaluation Conference, May 2020, Marseille, France. pp.6976-6982
We introduce Seshat, a new, simple and open-source software to efficiently manage annotations of speech corpora. The Seshat software allows users to easily customise and manage annotations of large audio corpora while ensuring compliance with the for
Externí odkaz:
http://arxiv.org/abs/2003.01472
Autor:
Garcia, Paola, Villalba, Jesus, Bredin, Herve, Du, Jun, Castan, Diego, Cristia, Alejandrina, Bullock, Latane, Guo, Ling, Okabe, Koji, Nidadavolu, Phani Sankar, Kataria, Saurabh, Chen, Sizhu, Galmant, Leo, Lavechin, Marvin, Sun, Lei, Gill, Marie-Philippe, Ben-Yair, Bar, Abdoli, Sajjad, Wang, Xin, Bouaziz, Wassim, Titeux, Hadrien, Dupoux, Emmanuel, Lee, Kong Aik, Dehak, Najim
This paper presents the problems and solutions addressed at the JSALT workshop when using a single microphone for speaker detection in adverse scenarios. The main focus was to tackle a wide range of conditions that go from meetings to wild speech. We
Externí odkaz:
http://arxiv.org/abs/1912.00938
Autor:
Bredin, Hervé, Yin, Ruiqing, Coria, Juan Manuel, Gelly, Gregory, Korshunov, Pavel, Lavechin, Marvin, Fustes, Diego, Titeux, Hadrien, Bouaziz, Wassim, Gill, Marie-Philippe
We introduce pyannote.audio, an open-source toolkit written in Python for speaker diarization. Based on PyTorch machine learning framework, it provides a set of trainable end-to-end neural building blocks that can be combined and jointly optimized to
Externí odkaz:
http://arxiv.org/abs/1911.01255
Autor:
Gallezot, Charlotte, Riad, Rachid, Titeux, Hadrien, Lemoine, Laurie, Montillot, Justine, Sliwinski, Agnes, Bagnou, Jennifer Hamet, Cao, Xuan Nga, Youssov, Katia, Dupoux, Emmanuel, Bachoud Levi, Anne-Catherine
Publikováno v:
In Cortex October 2022 155:150-161
Autor:
Riad, Rachid, Titeux, Hadrien, Cao, Xuan Nga, Dupoux, Emmanuel, Lemoine, Laurie, Montillot, Justine, Sliwinski, Agnes, Bagnou, Jennifer Hamet, Anne-Catherine Bachoud-Lévi
Publikováno v:
SLPAT 2022-9th Workshop on Speech and Language Processing for Assistive Technologies
SLPAT 2022-9th Workshop on Speech and Language Processing for Assistive Technologies, May 2022, Dublin, Ireland
Web of Science
SLPAT 2022-9th Workshop on Speech and Language Processing for Assistive Technologies, May 2022, Dublin, Ireland
Web of Science
International audience; Conversations between a clinician and a patient, in natural conditions, are valuable sources of information for medical follow-up. The automatic analysis of these dialogues could help extract new language markers and speed up
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7511dbe6ec9b204fa23ffa278fd633ef
https://hal.inria.fr/hal-03831674
https://hal.inria.fr/hal-03831674