R
Régine Le Bouquin-Jeannès
Researcher at University of Rennes
Publications - 25
Citations - 681
Régine Le Bouquin-Jeannès is an academic researcher from University of Rennes. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 10, co-authored 18 publications receiving 655 citations. Previous affiliations of Régine Le Bouquin-Jeannès include French Institute of Health and Medical Research.
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Linear and nonlinear causality between signals: methods, examples and neurophysiological applications
TL;DR: The results show that LGC, DCOH and PDC are not very robust in relation to nonlinear linkages but they seem to correctly find linear linkages if only the autoregressive parts are nonlinear.
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Seizures of temporal lobe epilepsy: identification of subtypes by coherence analysis using stereo-electro-encephalography.
Fabrice Bartolomei,Fabrice Wendling,Jean-Pierre Vignal,Sylvia Kochen,Jean-Jacques Bellanger,Jean-Michel Badier,Régine Le Bouquin-Jeannès,Patrick Chauvel +7 more
TL;DR: The existence of numerous interactions between medial limbic structures and the neocortex during TLE seizures is demonstrated, which could have implications for surgical strategies and the prognosis of epilepsy surgery, particularly when limited resection is indicated.
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Study of a voice activity detector and its influence on a noise reduction system
TL;DR: In the case of spatially uncorrelated (or slightly correlated) noises, a new technique based on the coherence function which is used to determine a speech/noise classification algorithm is introduced and it is concluded that they are quite comparable to those obtained using a manual labelling.
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On the evaluation of the conversational speech quality in telecommunications
Marie Guéguin,Régine Le Bouquin-Jeannès,Valérie Gautier-Turbin,Gérard Faucon,Vincent Barriac +4 more
TL;DR: The conversational model achieves high performance as revealed by comparison with the test results and with the existing standard methodology "E-model," presented in the ITU-T (International Telecommunication Union) Recommendation G.107.
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A two-sensor noise reduction system: applications for hands-free car kit
TL;DR: A two-microphone speech enhancer designed to remove noise in hands-free car kits using speech correlation and noise decorrelation to separate speech from noise, showing the superiority of the two-sensor approach to single microphone techniques.