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Team

COGNITIVE ROBOTICS, INTERACTIVE SYSTEMS, & SPEECH PROCESSING
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)




Latest publications of team

Multichannel Identification and Nonnegative Equalization for Dereverberation and Noise Reduction based on Convolutive Transfer Function

Xiaofei Li, Sharon Gannot, Laurent Girin, Radu Horaud. Multichannel Identification and Nonnegative Equalization for Dereverberation and Noise Reduction based on Convolutive Transfer Function. IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2018, pp.1-14. 〈10.1109/TASLP.2018.2839362〉. 〈hal-01645749v3〉

Automatic segmentation of speech articulators from real-time midsagittal MRI based on supervised learning

Mathieu Labrunie, Pierre Badin, Dirk Voit, Arun Joseph, Jens Frahm, et al.. Automatic segmentation of speech articulators from real-time midsagittal MRI based on supervised learning. Speech Communication, Elsevier : North-Holland, 2018, 99, pp.27 - 46. 〈10.1016/j.specom.2018.02.004〉. 〈hal-01758873〉

Multisource MINT Using the Convolutive Transfer Function

Xiaofei Li, Sharon Gannot, Laurent Girin, Radu Horaud. Multisource MINT Using the Convolutive Transfer Function. IEEE International Conference on Acoustic, Speech and Signal Processing, Apr 2018, Calgary, Alberta, Canada. 〈hal-01718106〉


All publications of team
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