1 code implementation • MMMPIE (COLING) 2022 • Juan Manuel Coria, Mathilde Veron, Sahar Ghannay, Guillaume Bernard, Hervé Bredin, Olivier Galibert, Sophie Rosset
Knowledge transfer between neural language models is a widely used technique that has proven to improve performance in a multitude of natural language tasks, in particular with the recent rise of large pre-trained language models like BERT.
no code implementations • LREC 2022 • Paul Lerner, Juliette Bergoënd, Camille Guinaudeau, Hervé Bredin, Benjamin Maurice, Sharleyne Lefevre, Martin Bouteiller, Aman Berhe, Léo Galmant, Ruiqing Yin, Claude Barras
With 16 TV and movie series, Bazinga!
1 code implementation • 24 Oct 2022 • Marvin Lavechin, Marianne Métais, Hadrien Titeux, Alodie Boissonnet, Jade Copet, Morgane Rivière, Elika Bergelson, Alejandrina Cristia, Emmanuel Dupoux, Hervé Bredin
Most automatic speech processing systems are sensitive to the acoustic environment, with degraded performance when applied to noisy or reverberant speech.
1 code implementation • 14 Sep 2021 • Juan M. Coria, Hervé Bredin, Sahar Ghannay, Sophie Rosset
We propose to address online speaker diarization as a combination of incremental clustering and local diarization applied to a rolling buffer updated every 500ms.
2 code implementations • 8 Apr 2021 • Hervé Bredin, Antoine Laurent
Experiments on multiple speaker diarization datasets conclude that our model can be used with great success on both voice activity detection and overlapped speech detection.
1 code implementation • 26 May 2020 • Marvin Lavechin, Ruben Bousbib, Hervé Bredin, Emmanuel Dupoux, Alejandrina Cristia
Spontaneous conversations in real-world settings such as those found in child-centered recordings have been shown to be amongst the most challenging audio files to process.
1 code implementation • 31 Mar 2020 • Juan M. Coria, Hervé Bredin, Sahar Ghannay, Sophie Rosset
Despite the growing popularity of metric learning approaches, very little work has attempted to perform a fair comparison of these techniques for speaker verification.
no code implementations • 6 Nov 2019 • Md Sahidullah, Jose Patino, Samuele Cornell, Ruiqing Yin, Sunit Sivasankaran, Hervé Bredin, Pavel Korshunov, Alessio Brutti, Romain Serizel, Emmanuel Vincent, Nicholas Evans, Sébastien Marcel, Stefano Squartini, Claude Barras
This paper describes the speaker diarization systems developed for the Second DIHARD Speech Diarization Challenge (DIHARD II) by the Speed team.
3 code implementations • 4 Nov 2019 • Hervé Bredin, Ruiqing Yin, Juan Manuel Coria, Gregory Gelly, Pavel Korshunov, Marvin Lavechin, Diego Fustes, Hadrien Titeux, Wassim Bouaziz, Marie-Philippe Gill
We introduce pyannote. audio, an open-source toolkit written in Python for speaker diarization.
Ranked #1 on Speaker Diarization on ETAPE
1 code implementation • 23 Oct 2019 • Marvin Lavechin, Marie-Philippe Gill, Ruben Bousbib, Hervé Bredin, Leibny Paola Garcia-Perera
In the in-domain scenario where the training and test sets cover the exact same domains, we show that the domain-adversarial approach does not degrade performance of the proposed end-to-end model.
Audio and Speech Processing I.2.7
1 code implementation • 23 Jul 2019 • Qingjian Lin, Ruiqing Yin, Ming Li, Hervé Bredin, Claude Barras
More and more neural network approaches have achieved considerable improvement upon submodules of speaker diarization system, including speaker change detection and segment-wise speaker embedding extraction.
6 code implementations • 14 Sep 2016 • Hervé Bredin
TristouNet is a neural network architecture based on Long Short-Term Memory recurrent networks, meant to project speech sequences into a fixed-dimensional euclidean space.