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Team manager : Gérard BAILLYThomas HUEBER


CRISSP team conducts theoretical, experimental and technological researches in the field of speech communication. More precisely, we aim at: 

    • Modeling verbal and co-verbal speech signal in face-to-face interaction involving humans, virtual avatar (talking head) and humanoid robots.
    • Understanding the human speech production process by modeling relationships between speech articulation and speech acoustics.
    • Studying communication of people with hearing impairment.
    • Designing speech technologies for handicapped people, language learning, and multimedia.




The 3 research axis of the CRISSP team are:

    • Cognitive robotics: improve socio-communicative skills of humanoid robots. 
    • Interactive systems: design real-time/reactive communicative systems exploiting the different modalities of speech (audio, visual, gesture, etc.).
    • Speech processing: articulatory synthesis, acoustic-articulatory inversion, speech synthesis, voice conversion.

Domains of expertise of CRISSP team

    • Audio signal processing (analysis, coding, denoising, source separation)
    • Speech processing (analysis, transformation, conversion/morphing, text-to-speech synthesis, articulatory synthesis/inversion)
    • Statistical machine learning
    • Acquisition of multimodal articulatory data (using electromagnetic articulography, ultrasound imaging, MRI, EMG, etc.)
    • Acquisition of social signals (eye gaze, body posture, head movements, etc.) during face-to-face interaction


Team members

(updated 18/12/2015)


Contact : Gérard Bailly et Thomas Hueber (mail : firstname.lastname@gipsa-lab.fr)

Last publications of team

Motion planning for robot audition

Quan V. Nguyen, Francis Colas, Emmanuel Vincent, François Charpillet. Motion planning for robot audition. Autonomous Robots, Springer Verlag, 2019, 43 (8), pp.2293-2317. ⟨10.1007/s10514-019-09880-1⟩. ⟨hal-02188342⟩

Variational Bayesian Inference for Audio-Visual Tracking of Multiple Speakers

Yutong Ban, Xavier Alameda-Pineda, Laurent Girin, Radu Horaud. Variational Bayesian Inference for Audio-Visual Tracking of Multiple Speakers. IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2019, 42, pp.1-17. ⟨10.1109/TPAMI.2019.2953020⟩. ⟨hal-01950866v2⟩

Audio-Visual Variational Fusion for Multi-Person Tracking with Robots

Xavier Alameda-Pineda, Soraya Arias, Yutong Ban, Guillaume Delorme, Laurent Girin, et al.. Audio-Visual Variational Fusion for Multi-Person Tracking with Robots. ACMMM 2019 - 27th ACM International Conference on Multimedia, Oct 2019, Nice, France. pp.1059-1061, ⟨10.1145/3343031.3350590⟩. ⟨hal-02354514⟩

Voir toutes les publications de l'équipe dans HAL
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