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Éric Plourde

Professeur, Faculté de génie

FAC. GÉNIE Électrique et informatique

Présentation

Sujet de recherche

Transmission and Processing of Numerical Signals, Auditory System

Disciplines de recherche

Electrical Engineering and Electronic Engineering, Biomedical Engineering and Biochemical Engineering

Mots-clés

Spiking Neural Networks, Speech Processing, Neural Signal Processing, Statistical Signal Processing, Computational Neuroscience, Speech Enhancement, Neural implants, Brain-machine interface, Neural Signal Modeling

Intérêts de recherche

• Spiking Neural Networks (Applications to Speech Processing) • Speech Processing (Speech Enhancement, Speech Coding, Biologically Inspired Speech Processing) • Statistical Signal Processing (Bayesian Estimation, Point Process Analysis) • Neural Signal Processing (Neural Spike Train Modeling, Characterization of Neural Discharges in the Auditory System) • Biomedical Instrumentation (Auditory Brain Implants, Cardiac Impedance Probes, Computer Assisted Surgery)

Langues parlées et écrites

Anglais, Français

Diplômes

(2011). (Post-doctorate, Postdoctoral Fellowship). Massachusetts Institute of Technology.

(2009). Bayesian short-time spectral amplitude estimators for single-channel speech enhancement (Doctorate, Ph.D.). McGill University.

(2004). (Diploma, Diploma in Postsecondary Education). Université de Montréal.

(2003). Mesures in vivo de l’impédance du myocarde durant l’ischémie et détermination de ses résistivités électriques intracellulaires et extracellulaire (Master's Thesis, M.A.Sc.). École Polytechnique de Montréal.

(2003). (Bachelor's, B.Eng.). École Polytechnique de Montréal.

(1995). (Diploma, Diploma in Health Sciences). Université de Moncton.

Expérience académique

Professeur titulaire. (2021-). Université de Sherbrooke. Canada.

Professeur agrégé. (2016-2021). Université de Sherbrooke. Canada.

Professeur adjoint. (2011-2016). Université de Sherbrooke. Canada.

Prix et distinctions

  • Prix du mérite Jacques-Bazinet 2014 - Génie informatique. Association générale des étudiants de génie de l'Université de Sherbrooke. (Prize / Award).
  • Prix du mérite Jacques-Bazinet 2016 - Génie informatique. Association générale des étudiants de génie de l'Université de Sherbrooke. (Prize / Award).

Publications

Articles de revue

  • *Hosseini, M; Celotti, L; Plourde, E. (2022). End-to-end brain-driven speech enhancement in multi-talker conditions. IEEE/ACM Transactions on Audio, Speech and Language Processing 30 1718-1733. (Published).
  • *Hosseini, M; Rodriguez, G; Guo, H; Lim, HH; Plourde, E. (2021). The effects of different input noises on the activity of auditory neurons using GLM-based metrics. Journal of Neural Engineering 17 p. (Published).
  • *Moinnereau MA, Rouat J, Whittingstall K, Plourde E. (2020). A frequency-band coupling model of EEG signals can capture input audio information. Hearing Research 393 9 p. (Published).
  • *Moinnereau MA, Whittingstall K, Plourde E. (2019). Electroencephalogram (EEG) recordings obtained when simultaneously presenting audio stimulations. IEEE DataPort DOI: 10.21227/e90n-s (Published).
  • *Moinnereau MA, *Brienne T, Brodeur S, Rouat J, Whittingstall K, Plourde E. (2018). Classification of auditory stimuli from EEG signals with a regulated recurrent neural network reservoir. arXiv.org 5 p. (Published).
  • *Chung H, Badeau R, Plourde E, Champagne B. (2018). Training and compensation of class-conditioned NMF bases for speech enhancement. Neurocomputing 284 107-118. (Published).
  • *Chung H, Plourde E, Champagne B. (2017). Regularized non-negative matrix factorization with Gaussian mixtures and masking effects for speech enhancement. Speech Communication 87 18-30. (Published).
  • Adeli M, Rouat J, Wood S, Molotchnikoff S, Plourde E. (2016). A flexible bio-inspired hierarchical model for analyzing musical timbre. IEEE/ACM Transactions on Audio, Speech and Language Processing 24 (5), 875-889. (Published).
  • *Chung H, Plourde E, Champagne B. (2016). Discriminative training of NMF model based on class probabilities for speech enhancement. IEEE Signal Processing Letters 23 (4), 502-506. (Published).
  • Parchami M, Zhu WP, Champagne B, Plourde E. (2016). Recent developments in speech enhancement in the short-time Fourier transform domain. IEEE Circuits and Systems Magazine 16 (3), 45-77. (Published).
  • Parchami M, Zhu W-P, Champagne B, Plourde E. (2015). Bayesian STSA estimation using masking properties and generalized Gamma prior for speech enhancement. EURASIP Journal on Advances in Signal Processing (87), 21 p. (Published).
  • Plourde E, Delgutte B, Brown E N. (2011). A point process model for auditory neurons considering both their intrinsic dynamics and the spectro-temporal properties of an extrinsic signal. IEEE Transactions on Biomedical Engineering 58 (6), 1507-1510. (Published).
  • Plourde E, Champagne B. (2011). Multidimensional STSA estimators for speech enhancement with correlated spectral components. IEEE Transactions on Signal Processing 7 (59), 3013-3024. (Published).
  • Plourde E, Champagne B. (2009). Generalized Bayesian estimators of the spectral amplitude for speech enhancement. IEEE Signal Processing Letters 16 (6), 485-488. (Published).
  • Plourde E, Champagne B. (2008). Auditory based spectral amplitude estimators for speech enhancement. IEEE Transactions on Audio, Speech and Language Processing 16 (8), 1614-1623. (Published).

Rapports

  • Plourde E. (2010). Point process model of auditory nerve/cochlear nucleus spiking accounting for the baseline rate, spiking history and spectro-temporal properties of the input stimulus. Massachusetts Institute of Technology. 15 p.

Articles de conférence

  • *El Ferdaoussi, A; Rouat, J; Plourde, E. (2022). Optimizing spike encoding of speech using information theory for neuromorphic systems. Proc. Int. Conf. on Neuromorphic Systems (ICONS). United States, 4. (Submitted).
  • *Bahadi, S; Rouat, J; Plourde, E. (2021). Adaptive approach for sparse representations using the locally competitive algorithm for audio. Proc. IEEE International Workshop on Machine Learning for Signal Processing. Australia, 6. DOI. (Published).
  • *El Ferdaoussi, A; Plourde, E; Rouat, J. (2021). Audio frequency spike encoding methods evaluation through mutual information. 30th Annual Computational Neuroscience Meeting (CNS 2021). (Published).
  • *El Ferdaoussi, A; Plourde, E; Rouat, J. (2021). Information-theoretic investigation of sound to spike encoding algorithms. NeuroSymposium. (Published).
  • *Hosseini, M; Celotti, L; Plourde, E. (2021). Speaker-independant brain enhanced speech denoising. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 1310-1314. (Published).
  • *Hosseini M, Azadmanesh M, Plourde E. (2019). Effect of simultaneously stimulating different ganglion cell types with the same stimulation strategy in epiretinal implants. Int. Conf. of the IEEE Engineering in Medicine and Biology Society. 1 p. (Published).
  • *Hosseini M, Rodriguez G, Guo H, Lim HH, Plourde E. (2019). Novel metrics to measure the effect of additive inputs on the activity of sensory system neurons. Int. Conf. of the IEEE Engineering in Medicine and Biology Society. 5141-5145. (Published).
  • Rouat J, Plourde E, Brodeur S. (2019). Unsupervised regulation for the self-organized CRITICAL recurrent neural network: Implementation and validation of end to end EEG classification. INRC Winter Workshop. (Published).
  • *LeFlahat E, Billard JC, Plourde E. (2018). A comparison of ECG waveform features for the classification of normal and abnormal heartbeats. Computing in Cardiology. 4 p. (Published).
  • *Chung H, Plourde E, Champagne B. (2018). A supervised multi-channel speech enhancement algorithm based on Bayesian NMF model. IEEE Global Conf. on Signal and Information Process. (GlobalSIP). 221-225. (Published).
  • Lemaire W, Benhouria M, Koua K, Laplante E, Gauthier LP, Plourde E, Roy S, Fontaine R. (2018). Implant de neurostimulation rétinien. 1er Symposium québécois sur la neurostimulation. (Published).
  • *Chung H, Kim T, Plourde E, Champagne B. (2018). Noise-adaptive deep neural network for single-channel speech enhancement. IEEE Int. Workshop on Machine Learning for Signal Processing. 6 p. (Published).
  • *Hosseini M, Rodriguez G, Guo H, Lim HH, Plourde E. (2018). Noise processing in the central nucleus of the inferior colliculus. NeuroSymposium 2018. (Published).
  • *Hosseini M, Rodriguez G, Guo H, Lim H, Plourde E. (2018). The influence of noise on the spiking activity of inferior colliculus neurons under different stimulus levels and SNRs. Society for Neuroscience. (Published).
  • *Chung H, Plourde E, Champagne B. (2017). Single-channel enhancement of convolutive noisy speech based on discriminative NMF algorithm. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2302-2306. (Published).
  • *Bosco J, Plourde E. (2017). Speech enhancement using both spectral and spectral modulation domains. IEEE Canadian Conf. on Electrical and Computer Engineering (CCECE). 4 p. (Published).
  • *Chung H, Plourde E, Champagne B. (2016). Basis compensation in non-negative matrix factorization model for speech enhancement. IEEE Int. Conf. Acoustics, Speech, and Signal Processing (ICASSP). 2249-2253. (Published).
  • *Siahpoush S, Erfani Y, Rode T, Lim HH, Rouat J, Plourde E. (2015). Improving neural decoding in the central auditory system using bio-inspired spectro-temporal representations and a generalized bilinear model. 37th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society. 5146-5150. (Published).
  • *Ghodoosipour G, Plourde E, Champagne B. (2015). On the use of a codebook-based modeling approach for Bayesian STSA speech enhancement. 28th IEEE Canadian Conf. on Electrical and Computer Engineering (CCECE). 1277-1282. (Published).
  • Plourde E, Rode T, Lim HH. (2015). The contribution of trained parameters to the goodness of fit of a Bayesian neural encoding model for the auditory system. IEEE EMBS Neural Engineering Conference. 910-913. (Published).
  • Rouat J, Brodeur S*, Plourde E. (2014). Auditory object feature maps with a hierarchical network of independent components. BMC Neuroscience, vol. 15 (Supp. 1), 66. (Published).
  • *Chung H, Plourde E, Champagne B. (2014). Regularized NMF-based speech enhancement with spectral components modeled by Gaussian mixtures. IEEE Machine Learning for Signal Processing Workshop. 6 p. (Published).
  • Plourde E. (2014). The effect of trained parameters in Bayesian neural encoding models for the auditory system. BMC Neuroscience, vol. 15 (Supp. 1), 67. (Published).
  • *Valade F, Plourde E. (2013). Évaluation de la justesse de la détection en fonction du bruit dans le tri de décharges neuronales. Association francophone pour le savoir (ACFAS) Conference. (Published).
  • Plourde E, Rode T, Lim H H, Brown E N. (2012). A point process study of the spiking activity and dynamics of inferior colliculus neurons. Society for Neuroscience Meeting (SFN). (Published).
  • Plourde E, Brown E N. (2012). The effect of different spectro-temporal representations of an input auditory stimulus on the fitting of a point process model of auditory neurons. Proc. 11th Int. Conf. Information Sci., Signal Processing and their Applications (ISSPA), 799-803. (Published).
  • Plourde E, Delgutte B, Brown E N. (2011). The relative importance in the auditory nerve spiking of a neuron’s internal dynamics versus an external input stimulus. Proc. IEEE Engineering in Medicine and Biology Society Conf. on Neural Eng., 9-12. (Published).
  • Plourde E, Champagne B. (2010). A family of Bayesian STSA estimators for the enhancement of speech with correlated frequency components. Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing (ICASSP), 4766-4769. (Published).
  • Plourde E, Champagne B. (2009). Bayesian spectral amplitude estimation for speech enhancement with correlated spectral components. Proc. IEEE Workshop on Statistical Signal Processing, 397-400. (Published).
  • Plourde E, Champagne B. (2008). Perceptually based speech enhancement using the weighted beta-SA estimator. Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing (ICASSP), 4193-4196. (Published).
  • Plourde E, Champagne B. (2007). Integrating the cochlea’s compressive nonlinearity in the Bayesian approach for speech enhancement. Proc. 15th European Signal Processing Conf. (EUSIPCO), 70-74. (Published).

Autres contributions

Gestion d'évènements

  • Session Chair - Brain Connectivity II. (2020) IEEE International Symposium on Biomedical Imaging (ISBI). (Conference).
  • Membre, Comité organisateur (Panel Co-Chair). (2019) IEEE Global Conference on Signal and Information Processing (GlobalSIP). (Conference).
  • Membre, Comité organisateur (Publication Chair). (2017) 15th Canadian Workshop on Information Theory (CWIT). (Workshop).
  • Session Chair - Data Compression and Coding. (2017) 15th Canadian Workshop on Information Theory (CWIT). (Workshop).
  • Technical Program Area Editor (Bio-Imaging and Signal Processing). (2017) IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). (Conference).

Présentations

  • *Bahadi, S; Rouat, J. (2021). Audio-visual scene analysis with spike-based representations of SNN. INRC Intel Workshop. United States
  • *Hosseini, M; Celloti, L; Plourde, E. (2021). End to end speech enhancement with auditory attention via EEG. CogEar Workshop.
  • Fontaine R, Lemaire W, Martin-Hardy G, *Besrour M, Benhouria M, Koua K, *Lavoie J, Tong W, Stamp M, Garrett D, Prawer S, Plourde E, Roy S. (2020). Design and assembly considerations for an optical data and power link-based retinal implant. Stanford Mini-symposium on Electronic Replacement of Sight. Stanford, CA (en ligne), United States
  • Plourde E. (2019). Noisy speech processing: the brain vs. the algorithms. Harvard School of Engineering and Applied Sciences Electrical Engineering Seminar Series. Cambridge, United States
  • Plourde E. (2018). Neural encoding of visual information. iBIONICS Technical Seminars. Longueil, Canada
  • Fontaine R, Roy S, Plourde E. (2017). Retinal implant development. iBIONICS Technical Seminars. Ottawa, Canada
  • Plourde E. (2017). Speaking of neurons… speech and neural signal processing. ENB Symposium. Boston, United States
  • Plourde E. (2014). Encoding and decoding of neural signals from the auditory system. NSERC-CREATE Training Program in Integrated Sensor Systems Summer School. Montréal, Canada
  • (2013). Neural signal processing. Discovery of 3IT research activities. Sherbrooke, Canada
  • (2012). Statistical neural signal processing and its application to speech enhancement. NECOTIS-UdeM Multidisciplinary Colloquium. Sherbrooke, Canada
  • (2011). The statistical coding of neural spikes in the auditory pathway. NECOTIS-UdeM Multidisciplinary Colloquium. Montréal, Canada
  • (2011). The statistical processing of neural signals from the auditory system. Department of Electrical Engineering and Computer Engineering, Université de Sherbrooke. Sherbrooke, Canada
  • (2010). Neuroscience Statistics Research Laboratory : Neural signal processing and general anesthesia. Brain and Cognitive Science Research Day. Cambridge, United States
  • (2008). Auditory based Bayesian estimators for speech enhancement. Neuroscience Statistics Research Laboratory Seminar, M.I.T. Cambridge, United States
  • (2008). Perceptually based speech enhancement using the weighted beta-SA estimator. SYTACom Student's Day. Montréal, Canada