BAILLY
Gérard
Directeur de Recherche CNRS
Research
Human-Robot InteractionNina robot
Our iCub robot Nina was born on 2013 Oct 1st. Her biological parents are at the Italian Institute of Technology (IIT) in Genova. In collaboration with IIT, we developped a talking face with jaw and lips articulations. We are currently working on multimodal Human-Robot interaction, including robot-mediated Human-Human interaction via immersive téléoperation.
For further reading:
  1. Nguyen, D.-C., G. Bailly and F. Elisei (2017)  An evaluation Framework to Assess and Correct the Multimodal Behavior of a Humanoid Robot in Human-Robot Interaction, Gesture in Interaction (GESPIN), Posznan, Poland: pp. 56-62.
  2. Nguyen, D.-C., G. Bailly and F. Elisei (2016) Conducting neuropsychological tests with a humanoid robot: design and evaluation. IEEE Int. Conf. on Cognitive Infocommunications (CogInfoCom), Wroclaw, Poland, pp. 337-342.
  3. Foerster F., G. Bailly and F. Elisei (2015) Impact of iris size and eyelids coupling on the estimation of the gaze direction of a robotic talking head by human viewers. Humanoids, Seoul, Korea: pp.148-153. 
  4. Parmiggiani A., M. Randazzo, M. Maggiali, G. Metta, F. Elisei and G. Bailly  (2015) "Design and Validation of a Talking Face for the iCub", International Journal of Humanoid Robotics, 1550026:1-20.
  5. Bailly G., F. Elisei and M. Sauze (2015). Beaming the gaze of a humanoid robot. Human-Robot Interaction (HRI) Late Breaking Reports, Portland, OR: pp.47-49. 
  6. Boucher, J.-D., U. Pattacini, A. Lelong, G. Bailly, P. F. Dominey, F. Elisei, S. Fagel and J. Ventre-Dominey (2012) "I reach faster when I see you look: Gaze effects in human-human and human-robot face-to-face cooperation." Frontiers in neurorobotics 6(3), DOI: 10.3389/fnbot.2012.00003.
  7. Sauze, M., G. Bailly and F. Elisei (2014). Where are you looking at? Human perception of the gaze direction of a robotic talking head for situated interaction. Humanoids, Madrid.
Studying, modelling and tracking facial movements3D tongue
In line with the work initiated by the late Christian Benoît and thanks to a critical mass of researchers (my colleagues Pierre Badin and Frédéric Elisei, my former PhD students Mathias Odisio, Maxime Bérar, Pierre Gacon, Oxana Govokhina, in collaboration with Pierre-Yves Coulon and Michel Desvignes from LIS and Gaspard Breton from Orange Labs), we have developped multiple virtual clones of human speakers for different languages (French, English, German, Autraslian English, Japanase, etc). Original data-driven control, shape and appearance models have been developped that mimick the movements of visible - and also internal articulators - organs when speaking. The combination of speech and facial expressions that recruits the lower face (smiling, disgust) has also been studied. These models are used to analyse, synthesize and track audiovisual speech.
For further reading
  1. Bailly, G., O. Govokhina, F. Elisei and G. Breton (2009). "Lip-synching using speaker-specific articulation, shape and appearance models." Journal of Acoustics, Speech and Music Processing. Special issue on "Animating Virtual Speakers or Singers from Audio: Lip-Synching Facial Animation", ID 769494: 11 pages.
  2. Badin, P., Elisei F., Bailly, G., Savariaux, C., Serrurier, A. & Tarabalka, Y. (2007). "Têtes parlantes audiovisuelles virtuelles : Données et modèles articulatoires - applications." Revue de Laryngologie, 128(5), 289-295.
  3. Beautemps, D., P. Badin and G. Bailly (2001). Degrees of freedom in speech production: analysis of cineradio- and labio-films data for a reference subject, and articulatory-acoustic modeling. Journal of the Acoustical Society of America, 109(5): 2165-2180.
Face-to-face communicationdistribution of gaze among different regions of interest in the face according to various cognitive states
Gaze patterns. With Frédéric Elisei and Stephan Raidt, we have studied mutual gaze patterns during face-to-face conversations. We have shown that the cognitive states and respective roles of the interlocutors in the conversation has an impact on the distribution of fixations among the different regions of interest in the face (left or right eye, mouth, nose ridge, etc.) as well as blinking rate. Our aim is to develop not only talking heads but conversational agents that are aware of the mental states of its human interlocutor(s) and signal it by appropriate behaviour. 
For further reading:
  1. Boucher J.-D., U. Pattacini, A. Lelong, G. Bailly, P. F. Dominey, F. Elisei, S. Fagel and J. Ventre-Dominey (2012) "I reach faster when I see you look: Gaze effects in human-human and human-robot face-to-face cooperation", Frontiers in neurorobotics  6(3),
  2. Bailly, G., S. Raidt & F. Elisei (2010) "Gaze, conversational agents and face-to-face communication", Speech Communication - special issue on Speech and Face-to-Face Communication, 52(3): 598–612.
  3. Bailly, G., F. Elisei and S. Raidt (2008). "Boucles de perception-action et interaction face-à-face." Revue Française de Linguistique Appliquée XIII(2): 121-131.
Speech patterns. convergence
With Amélie Lelong, we have studied mutuial adaptation speech patterns during speech games named "speech dominos". This very simple game consists in chaining words that begin with the same syllabe as the last previously uttered word. We have shown that the degree of phonetic convergence - estimated with reference to words spelled alone - largely depend on previous exposure to your interlocutor (friends converge more than unknowns) and social relations (in particular dominance).
For further reading:
  1. Bailly G. and A. Martin (2014). Assessing objective characterizations of phonetic convergence. Interspeech, Singapour: pp.2011-2015. 
  2. Lelong, A. & G. Bailly (2012). Original objective and subjective characterization of phonetic convergence. International Symposium on Imitation and Convergence in Speech. Aix-en-Provence, France.
  3. Lelong, A. and G. Bailly (2011). Study of the phenomenon of phonetic convergence thanks to speech dominoes Analysis of Verbal and Nonverbal Communication and Enactment: The Processing Issue. A. Esposito, A. Vinciarelli, K. Vicsi, C. Pelachaud and A. Nijholt. Berlin, Springer Verlag: 280-293.
  4. Bailly G. & A. Lelong (2010). Speech dominoes and phonetic convergence. Interspeech. Tokyo, p.1153-1156. 
List of dominos for French & English (gracefully provided by Sankar Mukherjee et al): DOMINOES.xls
Modelling prosody
F0 contour for incredulous questionTogether with Véronique Aubergé, we have developped a prosodic model that directly encodes communicative functions by superposing and overlapping multiparametric prosodic contours. Plinio Barbosa demonstrated the existence of rhythmic contours encoding the hierarchy of syntactic constituents. These contours for French are not only characterized by a final lengthening depening of the importance of the syntactic break but by a gradual deceleration when considering the sequence of P-centers of the part-of-speech. We also proposed to consider the pause as an emergent phenomenon in the process of distributing the planned rhythm among the constituents of each syllable. Yann Morlec and Bleike Holm worked on trainable prosodic model able to recover and generate elementary multiparametric prosodic contours from the observation of multiple occurences thanks to statistical modelling. The trainable SFC (Superposition of Functional Contour) model was confronted to several languages (French, German, Spanish, Chinese, etc.) and various linguistic content including spoken maths.
For further reading:
  1. Bailly, G. and Holm, B. (2005) SFC: a trainable prosodic model. Speech Communication,46 (3-4). Special issue on Quantitative Prosody Modelling for Natural Speech Description and Generation - Edited by K. Hirose, D. Hirst and Y. Sagisaka): 348-364.
  2. Bailly, G. and B. Holm (2002). Learning the hidden structure of speech: from communicative functions to prosody. Cadernos de Estudos Linguisticos, 43: 37-54.
  3. Morlec, Y., G. Bailly and V. Aubergé (2001). Generating prosodic attitudes in French: data, model and evaluation. Speech Communication, 33(4): 357-371.
Augmented speech communication
F0 contour for incredulous questionTogether with Denis Beautemps, Pierre Badin and Thoams Hueber, we develop speech technologies that can help people with temporary or permanent motor or perceptual deficits or disabilities to communicate. These constraints may be due to cognitive or physiological handicaps of the interlocutors themselves, to impoverished communication channels or to adverse environnements. These technologies aim at enhancing, enriching or replacing the degraded communication signals with enhanced synthetic signals thanks to the priori knowledge of the intrinsic coherence of the multimodal signals. Potential sources of coherence comprise generic virtual talking heads that can be adapted to the speaker characteristics as well as  linguistic constraints that can used in the restauration process when the language being spoken is known. Such technologies include cued speech synthesis and recognition, acoustic-to-articulatory inversion, voice conversion. With Hélène Loevenbrück and in collaboration with Tomoki Toda from NAIST, Viet-Anh Tran has proposed an enhanced system for murmur-to-speech conversion with an application to silent speech communication. With Pierre Badin and in the framework of the ARTIS project, Atef Ben Youssef is working on data-driven statistical audiovsiual-to-articulatory inversion for language training.
For further reading:
  1. Hueber T. and G. Bailly (2015) "Statistical Conversion of Silent Articulation into Audible Speech using Full-Covariance HMM", Computer, Speech and Language, 36: 274–293.
  2. Heracleous P., P. Badin, G. Bailly and N. Hagita (2011) "A pilot study on augmented speech communication based on Electro-Magnetic Articulography", Pattern Recognition Letters, 32: 1119-1125.
  3. Badin P., Y. Tarabalka, F. Elisei & G. Bailly (2010) "Can you read tongue movements? Evaluation of the contribution of tongue display to speech understanding", Speech Communication - special issue on Speech and Face-to-Face Communication, 52(3): 493-503.
  4. Bailly, G., Badin, D. Beautemps & F. Elisei (2010). Speech technologies for augmented communication, in Computer-Synthesized Speech Technologies: Tools for Aiding Impairment. J. Mullenix and S. Stern. Hershey, PA, IGI Global: 116-128.
  5. Tran V.-A., G. Bailly & H. Loevenbruck (2010) "Improvement to a NAM-captured whisper-to-speech system", Speech Communication - special issue on Silent Speech Interfaces, 52(4): 314-326. 

Grenoble Images Parole Signal Automatique laboratoire

UMR 5216 CNRS - Grenoble INP - Université Joseph Fourier - Université Stendhal