Graduate School and Research Center in Digital Sciences

Nicholas EVANS

Nicholas EVANS
Nicholas EVANS
Eurecom - Digital Security 
Professor
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Teaching

  • From 2002-06 Nicholas Evans was an Assistant Professor at the University of Wales Swansea (UWS), where he taught courses in Communications, and remained an honorary lecturer until 2009.
  • In 2006 he moved to the Laboratoire Informatique d'Avignon at the Université d'Avignon et des Pays de Vaucluse where he taught courses in Image Processing and Digital Communications.

  • He moved to EURECOM in October 2007 where he now teaches courses in Essential Mathematical Methods for Engineers, and in Speech and Audio Processing.

My courses

  • MathEng / Fall 2017 - Essential Mathematical Methods for Engineers

    This course aims to present a treatment of mathematical methods suitable for engineering students who are interested in the rapidly advancing areas of signal analysis, processing, filtering and estimation. Significant current applications relate to, e.g., speech and audio, music, wired and wireless communications, instrumentation, multimedia, radar, sonar, control, biomedicine, transport and navigation.  The course presents a study of linear algebra,  probability, random variables, and analogue systems as a pre-requisite to material relating to sampled-data systems.  Time permitting, the final part of the course covers the concepts of random processes, the analysis of random signals, correlation and spectral density.

    Teaching and Learning Methods: The course is comprised of lectures, exercises and laboratory sessions.

    Course policies: This course is aimed at students who have NOT already completed preparatory classes.  Completion of all in-lecture examples is strongly advised.

  • Speech / Spring 2018 - Speech and audio processing

    This course provides an introduction to the automatic processing of speech and audio signals.  It starts with a treatment of the human speech production and perception mechanisms and looks at how our understanding of them has influenced attempts to process speech and audio signals automatically.  The course then considers the analysis, coding and parameterisation of signals in the case of different speech and audio processing tasks.  After an introduction to essential pattern recognition techniques, the course considers specific applications including speech recognition, speaker recognition and speaker diarization.  The course also includes a treatment of speech and audio coding, noise compensation and speech enhancement.

    Teaching and Learning Methods:

    The course is comprised of lectures and exercises and laboratory sessions.

    Course policies: Attendance of laboratory sessions is mandatory.

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Distinctions

  • In June 2016, he has received with his co-authors Massimiliano Todisco and Hector Delgado, the Best Paper Award for their paper "A new feature for automatic speaker verification anti-spoofing: Constant Q cepstral coefficients" (Odyssey 2016).
  • In Novembre 2013, he has received with his co-authors Xuran Zhao and Jean-Luc Dugelay, the Best Student Paper Award for the article "Unsupervised multi-view dimensionality reduction with application to audio-visual speaker retrieval".
  • He was elected to the IEEE Speech and Language Technical Committee in 2013.