Marion Girod-Roux, Thomas Hueber, Diandra Fabre, Silvain Gerber, Mélanie Canault, et al.. Rehabilitation of speech disorders following glossectomy, based on ultrasound visual illustration and feedback. Clinical Linguistics & Phonetics, Taylor & Francis, 2020, pp.1-18. ⟨ 10.1080/02699206.2019.1700310 ⟩. ⟨ hal-01977670 ⟩
Notes on the use of variational autoencoders for speech and audio spectrogram modeling
Laurent Girin, Fanny Roche, Thomas Hueber, Simon Leglaive. Notes on the use of variational autoencoders for speech and audio spectrogram modeling. DAFx 2019 - 22nd International Conference on Digital Audio Effects, Sep 2019, Birmingham, United Kingdom. pp.1-8. ⟨ hal-02349385 ⟩
Fanny Roche, Thomas Hueber, Samuel Limier, Laurent Girin. Autoencoders for music sound modeling : a comparison of linear, shallow, deep, recurrent and variational models. SMC 2019 - 16th Sound & Music Computing Conference, May 2019, Malaga, Spain. ⟨ hal-02349406 ⟩
Célise Haldin, Audrey Acher, Louise Kauffmann, Thomas Hueber, Emilie Cousin, et al.. Effet de la rééducation perceptivo-motrice sur la récupération de la parole chez deux patientes avec aphasie non fluente chronique post-AVC. Revue de neuropsychologie, neurosciences cognitives et cliniques, Montrouge : John Libbey Eurotext, 2019, 11 (1), pp.44-59. ⟨ 10.1684/nrp.2019.0485 ⟩. ⟨ hal-02134778 ⟩
Visual Recognition of Continuous Cued Speech Using a Tandem CNN-HMM Approach
Li Liu, Thomas Hueber, Gang Feng, Denis Beautemps. Visual Recognition of Continuous Cued Speech Using a Tandem CNN-HMM Approach. 19th Annual Conference of the International Speech Communication Association (Interspeech 2018), Sep 2018, hyderabad, India. ⟨ hal-01978344 ⟩
Electrophysiological evidence for Audio-visuo-lingual speech integration
Avril Treille, Coriandre Vilain, Jean-Luc Schwartz, Thomas Hueber, Marc Sato. Electrophysiological evidence for Audio-visuo-lingual speech integration. Neuropsychologia, Elsevier, 2018, 109, pp.126-133. ⟨ 10.1016/j.neuropsychologia.2017.12.024 ⟩. ⟨ hal-02074993 ⟩
Biosignal-Based Spoken Communication: A Survey
Tanja Schultz, Thomas Hueber, Michael Wand, Dean J. Krusienski, Christian Herff, et al.. Biosignal-Based Spoken Communication: A Survey. IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2017, 25 (12), pp.2257 - 2271. ⟨ 10.1109/TASLP.2017.2752365 ⟩. ⟨ hal-01652757 ⟩
Introduction to the Special Issue on Biosignal-Based Spoken Communication
Tanja Schultz, Thomas Hueber, Dean J. Krusienski, Jonathan S. Brumberg. Introduction to the Special Issue on Biosignal-Based Spoken Communication. IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2017, 25 (12), pp.2254 - 2256. ⟨ 10.1109/TASLP.2017.2768838 ⟩. ⟨ hal-01652752 ⟩
Célise Haldin, Audrey Acher, Louise Kauffmann, Thomas Hueber, Emilie Cousin, et al.. Speech recovery and language plasticity can be facilitated by Sensori-Motor Fusion (SMF) training in chronic non-fluent aphasia. A case report study. Clinical Linguistics & Phonetics, Taylor & Francis, 2017, 32 (7), pp.1 - 27. ⟨ 10.1080/02699206.2017.1402090 ⟩. ⟨ hal-01651198 ⟩
Automatic animation of an articulatory tongue model from ultrasound images of the vocal tract
Diandra Fabre, Thomas Hueber, Laurent Girin, Xavier Alameda-Pineda, Pierre Badin. Automatic animation of an articulatory tongue model from ultrasound images of the vocal tract. Speech Communication, Elsevier : North-Holland, 2017, 93, pp.63 - 75. ⟨ 10.1016/j.specom.2017.08.002 ⟩. ⟨ hal-01578315 ⟩
Prénom NOM | Date d'entrée en thèse | Sujet | Ecole doctorale |
GEORGES Marc-Antoine | 01/10/2019 | Hybrid Bayesian and deep neural modeling for weakly supervised | EDISCE |
OUAKRIM Yanis | 01/10/2021 | Reconnaissance en Langue des Signes continue pour la conception d’un serveur gestuel | EEATS |
SANKAR Sanjana | 01/02/2021 | Reconnaissance et Génération Automatique du Cued Speech utilisant l’apprentissage profond | EEATS |
STEPHENSON Brooke | 06/01/2020 | Incremental sequence-to-sequence mapping for speech generation using deep neural networks | EEATS |
Grenoble Images Parole Signal Automatique laboratoire
UMR 5216 CNRS - Grenoble INP - Université Joseph Fourier - Université Stendhal