278 citations
- University of TorontoCA3 papers
- Canada Research ChairsCA2 papers
- Laboratoire de Linguistique FormelleFR2 papers
- Université Paris CitéFR2 papers
- Brno University of TechnologyCZ1 paper
- Carnegie Mellon UniversityUS1 paper
- Combustion Research and Flow Technology (United States)US1 paper
- Craft Engineering Associates (United States)US1 paper
- Délégation Paris 7FR1 paper
- Électricité de France (France)FR1 paper
- Laboratoire de Neurosciences CognitivesFR1 paper
- Laboratoire d'Informatique de GrenobleFR1 paper
6 papers
The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling
Tu Anh Nguyen, Maureen de Seyssel, Patricia Rozé +5
We introduce a new unsupervised task, spoken language modeling: the learning of linguistic representations from raw audio signals without any labels, along with the Zero Resource S…
Vocal markers from sustained phonation in Huntington's Disease
Rachid Riad, Hadrien Titeux, Laurie Lemoine +5
Disease-modifying treatments are currently assessed in neurodegenerative diseases. Huntington's Disease represents a unique opportunity to design automatic sub-clinical markers, ev…
Training design fostering the emergence of new meanings toward unprecedented and critical events
Simon Flandin, Deli Salini, Artémis Drakos +1
Our research is part of a technological research program in adult education conducted in reference to the "course of action" program. Using the activity-sign hypothesis of this pro…
Identification of primary and collateral tracks in stuttered speech
Rachid Riad, Anne-Catherine Bachoud-Lévi, Frank Rudzicz +1
Disfluent speech has been previously addressed from two main perspectives: the clinical perspective focusing on diagnostic, and the Natural Language Processing (NLP) perspective ai…
The Zero Resource Speech Challenge 2019: TTS without T
Ewan Dunbar, Robin Algayres, Julien Karadayi +10
We present the Zero Resource Speech Challenge 2019, which proposes to build a speech synthesizer without any text or phonetic labels: hence, TTS without T (text-to-speech without t…
Fader Networks: Manipulating Images by Sliding Attributes
Guillaume Lample, Neil Zeghidour, Nicolas Usunier +3
This paper introduces a new encoder-decoder architecture that is trained to reconstruct images by disentangling the salient information of the image and the values of attributes di…