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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

Multiple-Speaker Localization Based on Direct-Path Features and Likelihood Maximization with Spatial Sparsity Regularization

Xiaofei Li, Laurent Girin, Radu Horaud, Sharon Gannot. Multiple-Speaker Localization Based on Direct-Path Features and Likelihood Maximization with Spatial Sparsity Regularization. [Research Report] INRIA Grenoble - Rhône-Alpes. 2017. <hal-01413417>

Feature extraction using multimodal convolutional neural networks for visual speech recogntiion

Eric Tatulli, Thomas Hueber. Feature extraction using multimodal convolutional neural networks for visual speech recogntiion. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Mar 2017, New Orleans, United States. pp.2971-2975. <hal-01485539>

An EM Algorithm for Joint Source Separation and Diarisation of Multichannel Convolutive Speech Mixtures

Dionyssos Kounades-Bastian, Laurent Girin, Xavier Alameda-Pineda, Sharon Gannot, Radu Horaud. An EM Algorithm for Joint Source Separation and Diarisation of Multichannel Convolutive Speech Mixtures. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Mar 2017, New Orleans, United States. 2017. <hal-01430761>


All publications of team
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