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Dr. Potamitis Ilyas
Assistant Professor
Head of Bioacoustic signal processing and pattern recognition applications Group

Department of Music Technology & Acoustics
Technological Educational Institute of Crete
E. Daskalaki - Perivolia, 74100 Rethymno - Crete, Greece
tel. +30 28310-21911, +30 28310-23747, fax 28310-58323
e-mail: potamitis@stef.teicrete.gr or potamitis@wcl.ee.upatras.gr

 

About

Ilyas Potamitis received his Diploma in Electrical and Computer Engineering from the University of Patras Greece, in 1995 achieving a mark of 8.03/10. From February 1998 to 2002, he was with the Wire Communications Laboratory, University of Patras, Greece, from where in 2002 he received his Ph.D degree in signal processing and audio pattern recognition. During 2002-2004 he held a post-doc research position at the same lab. Since 2005, he holds a faculty position as an Assistant Professor in the Technological Educational Institute of Crete in Greece. His research interests include signal processing of acoustic signals and pattern recognition applications. He holds more than 70 publications in peer-reviewed journals and conferences and more than 150 citations.

 

Scientific interests

Applications:

1. Automatic recognition of general audio events (acoustic surveillance),

2. Speech/speaker processing and recognition (voice activated appliances),

3. Detection and recognition of bioacoustic signals (insects, birds, amphibians, mammals),

4. Computational Ecology,

5. Single channel source separation

 

Theory:

1. Statistical Signal Processing,

2. Applied Probability theory and Stochastic Processes,

3. Pattern Recognition,

4. Bayesian Statistics,

5. Markov and Hidden Markov Models,

6. Markov Chain Monte Carlo,

7. Particle Filtering

 

Projects

Dr. Potamitis served as a full partner in the following projects:

  1. Greece – Montenegro Bilateral Cooperation Program (GSRT 2006-2008): Novel spectral estimation techniques for efficient bird song classification

2. Prometheus (FP7-ICT-214901-2007): Prediction and interpretation of human behaviour based on probabilistic structures and heterogeneous sensors

3. Automatic Bioacoustic Detection of Rhynchophorus Ferrugineus (Lasithi perfecture, Crete, 2008-2009): A piezoelectric probe is inserted in the tree trunk and peeks up feeding vibrations of Rhynchophorus Ferrugineus that are classified by machine learning techniques. See associated freely distributed software http://www.wcl.ece.upatras.gr/ganchev/RPWd_gr.html

4. AMIBIO Automatic acoustic monitoring and inventorying of biodiversity (01/02/2010-30/06/2013), LIFE+08 NAT/GR/000539.

 

Group’s Hardware & Software

Our group makes extensive use of the following hardware & software:

 Hardware:

  1. AED 2000L (http://www.aeconsulting.com/aed-2000.html): Piezoelectric probes and amplifier/detector system used for insect detection (stored products and Rhynchophorus Ferrugineus).

  2. Autonomus field recorder Wildlife Acoustics (http://www.wildlifeacoustics.com): Automated monitoring of birds, frogs, and other wildlife populations.

  3. Parabolic microphone Telinga (http://www.telinga.com/): Monitoring of birds, frogs, and other wildlife populations.

  4. Ultrasound Microphones for the Avisoft-Bioacoustics UltraSoundGate Devices.

 Software:

  1. Song Scope Bioacoustics Monitoring Software Wildlife Acoustics (http://www.wildlifeacoustics.com): Song Scope software automatically detects and identifies birds, frogs, and other wildlife vocalizations in field recordings using sophisticated patented digital signal processing algorithms.

  2. HTK Hidden Markov Toolkit (http://htk.eng.cam.ac.uk/): The Hidden Markov Model Toolkit (HTK) is a portable toolkit for building and manipulating hidden Markov models. HTK is primarily used for speech recognition research.

  3. Raven Pro (http://www.birds.cornell.edu/brp/raven/RavenOverview.html): Raven is a software program for the acquisition, visualization, measurement, and analysis of bioacoustic signals.

  4. Avisoft SASLab Pro (http://www.avisoft.com/). Software for investigating animal sound communication.

  5. CoolEdit Pro (http://www.adobe.com/): General Sound Processing & Editing.

  6. Matlab (http://www.mathworks.com/): Can’t live without Matlab.

 

Sample publications

Acoustic surveillance:

[1] Stavros Ntalampiras, I. Potamitis, Nikos Fakotakis, “An Adaptive Framework for Acoustic Monitoring of Potential Hazards”, EURASIP Journal on Audio, Speech, and Music Processing Volume 2009 (2009), Article ID 594103, doi:10.1155/2009/594103, http://www.hindawi.com/journals/asmp/2009/594103.html

[2] Stavros Ntalampiras, I. Potamitis, Nikos Fakotakis, “Exploiting Temporal Feature Integration for Generalized Sound Recognition”, EURASIP Journal on Advances in Signal Processing. http://www.hindawi.com/journals/asp/aip.807162.html

 

Bioacoustic signal processing:

[3] I. Potamitis, Todor Ganchev, Dimitris Kododimas, “On automatic bioacoustic detection of pests: the cases of Rhynchophorus Ferrugineus and Sitophilus Oryzae”, Journal of Economic Entomology, Volume 102, Number 4 (10), pp. 1681-1690, August 2009.

          [4] T. Ganchev, I. Potamitis, “Automatic Acoustic Identification of Singing Insects”, Bioacoustics, Vol. 16, pp. 281–327, 2007.

 

Speech/speaker processing and recognition:

         [5] I. Potamitis et al., “Speech Separation of Multiple Moving Speakers Using Multi-Sensor Multi-Target Techniques”, IEEE Transactions on Systems Man and Cybernetics – A, Vol. 37, Issue: 1, pp. 72-81, Jan. 2007.

         [6] T. Giannakopoulos, N.A. Tatlas, T. Ganchev, I. Potamitis, “A Practical, Real-Time Speech-Driven Home Automation Front-end”, IEEE Transactions on Consumer Electronics, Vol. 51, No. 2, pp. 514-523, May 2005.

        [7] I. Potamitis, H. Chen, G. Tremoulis, “Tracking of Multiple Moving Speakers with Multiple Microphone Arrays”, IEEE Transactions on Speech and Audio Processing, Vol. 12, No. 5, pp. 520-529, September 2004.

          [8] I. Potamitis, E. Fishler, “Speech Activity Detection and Enhancement of a Moving Speaker Based on the Wideband Generalized Likelihood Ratio and Microphone Arrays”, Journal of the Acoustical Society of America, Vol. 116, No. 4, Pt. 1, pp. 2406-2415, October 2004.

        [9] I. Potamitis, “Estimation of Speech Presence Probability in the field of Microphone Array”, IEEE Signal Processing Letters, Vol. 11, No. 12, pp. 956-959, December 2004.

        [10] T. Ganchev, I. Potamitis, N. Fakotakis, G. Kokkinakis, “Text-Independent Speaker Verification for Real, Fast-Varying Noisy Environments”, International Journal of Speech Technology, Kluwer Academic Publishers, 7 (4), pp. 281-292, October 2004.

 

 

 

Single channel source separation:

         [11] I. Potamitis, “Single channel enumeration and recognition of an unknown and time-varying number of sound sources”, EUSIPCO, 16th European Signal Processing Conference, August 25-29, Laussane, Switzerland, 2008.

         [12] I. Potamitis, A. Ozerov, “Single channel source separation using static and dynamic features in the power domain”, EUSIPCO, 16th European Signal Processing Conference, August 25-29, Laussane, Switzerland, 2008.