Srikanth Madikeri

Short Biography

Srikanth Madikeri got his Ph.D. in Computer Science and Engineering from Indian Institute of Technology Madras in 2013. During his Ph.D., he worked on automatic speaker recognition and spoken keyword spotting. He is currently working as a Researche Associate at Idiap in the Speech Processing group. His current research interests include - Automatic Speech Recognition, Automatic Speaker Recognition and Speaker Diarization.

Education

  • Ph.D. in Computer Science and Engineering at IIT-Madras (2008-2013)
  • Bachelor of Engineering in Computer Science and Engineering, Anna University, Chennai (2004-2008)

Professional Experience

  • 2 years as Project Associate at IIT Madras (2008-2010)
  • 3 years as Research Associate at IIT Madras (2010-2013)
  • Postdoctoral researcher at Idiap Reserach Institute (2013-2018)
  • Research Associate at Idiap Reserach Institute (2018-present)

Publications

Journals

  • I. Himawan, S. Madikeri, P. Motlicek, M. Cernak, S. Sridharan, and C. Fookes, "Voice Presentation Attack Detection Using Convolutional Neural Networks", Handbook of Biometric Anti-Spoofing, pp. 391-415.
  • S. Dey, P. Motlicek, S. Madikeri, M. Ferras, "Template-matching for text-dependent speaker verification", Speech Communication, Vol 88, pp. 96-105.
  • M. Ferras, S. Madikeri, P. Motlicek, S. Dey and H. Bourlard, "A large-scale open-source acoustic simulator for speaker recognition", IEEE Signal Processing Letters, Vol. 23 (4), pp. 527-531.
  • S. Madikeri, "A fast and scalable hybrid FA/PPCA-based framework for speaker recognition", in Digital Signal Processing, Vol. 32, pp. 137-145, September 2014.
  • S. Madikeri, A. Talambedu, and H. A. Murthy, "Modified group delay feature based total variability space modelling for speaker recognition", Internation Journal of Speech Technology, Vol. 18(1), pp. 17-23.

Conferences (selected)

  • S. Dey, S. Madikeri, and P. Motlicek, "End-to-end text-dependent speaker verification using novel distance measures", in Proc. of Interspeech 2018, pp. 3598-3602.
  • S. Madikeri, S. Dey, and P. Motlicek, "Analysis of Language Dependent Front-End for Speaker Recognition", in Proc. of Interspeech 2018, pp. 1101-1105.
  • S. Dey, S. Madikeri, and P. Motlicek, "Information theoretic clustering for unsupervised domain-adaptation", in Proc. of ICASSP 2016, pp. 5580-5584.
  • M. Ferras, S. Madikeri, P. Motlicek, and H. Bourlard, "System fusion and speaker linking for longitudinal diarization of tv shows", in Proc. of ICASSP 2016, pp. 5495-5499.
  • S. Dey, S. Madikeri, M. Ferras, and P. Motlicek, "Deep neural network based posteriors for text-dependent speaker verification", in Proc. of ICASSP 2016, pp. 5050-5054.
  • N. Dawalatabad, S. Madikeri, C. C. Sekhar, and H. A. Murthy, "Two-Pass IB Based Speaker Diarization System Using Meeting-Specific ANN Based Features", in Proc. of Interspeech 2016, pp. 2199-2203.
  • M. Ferras, S. Madikeri, S. Dey, P. Motlicek, and H. Bourlard, "Inter-Task System Fusion for Speaker Recognition", in Proc. of Interspeech 2016, pp. 1810-1814.
  • S. Madikeri, and H. Bourlard, "KL-HMM based speaker diarization system for meetings", in Proc. of ICASSP 2015, Brisbane, Australia, pp. 4435-4439.
  • P. Motlicek, S.Dey, S. Madikeri, and L. Burget, "Employment of Subspace Gaussian Mixture Models in speaker recognition", in Proc. of ICASSP 2015, Brisbane, Australia, pp. 4445-4449.
  • I. Himawan, P. Motlicek, M. Ferras, S. Madikeri, "Towards utterance-based neural network adaptation in acoustic modeling", in Proc. of IEEE ASRU 2015.
  • S. Madikeri, and H. Bourlard ,"Filterbank slope based features for speaker diarization", in Proc. ICASSP 2014, Florence, Italy, pp. 111-115.
  • S. Madikeri, "Speaker Verification and Keyword Spotting Systems for Forensic Applications", Ph.D. thesis, IIT Madras.
  • S. Madikeri, "A Hybrid Factor Analysis and Probabilistic PCA-based system for Dictionary Learning and Encoding for Robust Speaker Recognition", In Odyssey 2012-The Speaker and Language Recognition Workshop [pdf].
  • S. Madikeri and H. A. Murthy, "Mel Filter Bank energy-based Slope feature and its application to speaker recognition," Communications (NCC), 2011 National Conference on , vol., no., pp.1-4, 28-30 Jan. 2011 doi: 10.1109/NCC.2011.5734713
  • S. Madikeri, and H. A. Murthy, "Discriminative training of Gaussian mixture speaker models: A new approach," Communications (NCC), 2010 National Conference on , vol., no., pp.1-5, 29-31 Jan. 2010 doi: 10.1109/NCC.2010.5430204

The full list of publications can be found here

Toolkits

Professional Activities and Awards

  • Winner of the International Create Challenge 2017
  • Best paper award at NCC 2011 for the paper titled "Discriminative training of Gaussian mixture speaker models: A new approach" in the Signal Processing Track

Contact

E-mail: firstname dot lastname at idiap dot ch

Tel: +41 27 721 7743
Office: 304-4
Contact