Senior Research Associate
Mathematik und Signalverarbeitung in der Akustik
Maschinelles Lernen in der Akustik

Tel. +43 1 51581-2532
Email: nicki.holighaus(at)oeaw.ac.at

Wissenschaftliche IDs:
ORCID: 0000-0003-3837-2865
Google Scholar: Nicki Holighaus
ResearchGate: researchgate.net/profile/Nicki_Holighaus

 

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Nicki Holighaus studierte Mathematik und theoretische Informatik an der Justus–Liebig–Universität zu Gießen, Deutschland. Nach dem Abschluss im Jahr 2010 begann er das Dokrotratsstudium an der Universität Wien, Österreich, dass er im Oktober 2013 mit der Verteidigung seiner Doktorarbeit "Theory and implementation of adaptive time-frequency transforms” erfolgreich abschloss. Während seines Studiums and the Universität Wien arbeitete er dort als Forschungsassistent in der Numerical Harmonic Analysis Group (NuHAG). 

Seit August 2012 ist er Mitglied der Gruppe "Mathematics and Signal Processing in Acoustics" des Instituts für Schallforschung. Dort arbeitet er an theoretischen und angewandten Aspekten adaptierter Zeit-Frequenz Darstellungen und anderer Frames.

Derzeitige Forschung


Seine Forschungsinteressen konzentrieren sich auf die Verwendung von Zeit-Frequenz-Methoden für Signalverarbeitung. Insbesondere forscht er in den Bereichen Zeit-Frequenz-Analyse, mathematische Theorie und Design adaptiver und adaptierter Zeit-Frequenz-Darstellungen, Zeit-Frequency-Verarbeitung in der Akustik und Verwendung von Zeit-Frequenz-Darstellungen in maschinellem Lernen für akustische Signalverarbeitung.

Aktuelle Forschungsprojekte: MERLIN

Aktuelle Themen:

  • Theory and application of warped time-frequency representations 
  • Function spaces and discretization for structured continuous frames
  • Structure of time-frequency phase
  • Signal processing with time-frequency phase
  • Deep learning with time-frequency features
  • Neural audio generation
  • Audio inpainting with generative neural networks
  • Time-frequency processing and perception

Publikationen

Publikationen

  • Holighaus, N.; Wiesmeyr, C.; Pruša, Z. (2020) A Class of Warped Filter Bank Frames Tailored to Non-linear Frequency Scales. Journal of Fourier Analysis and Applications, Bd. 26.
  • Balazs, P.; Holighaus, N. (2020) LTFAT - Die Zeit-Frequenz Toolbox., Jubiläumstagungsband DAGA 2020.
  • Marafioti, A.; Holighaus, N.; Majdak, P.; Perraudin, N. (2019) Audio inpainting of music by means of neural networks., 146th Convention of the Audio Engineering Society; Dublin.
  • N., Holighaus; Koliander, G.; Pruša, Z.; Abreu, L. D. (2019) Characterization of Analytic Wavelet Transforms and a New Phaseless Reconstruction Algorithm. IEEE Transactions on Signal Processing, Bd. 67, S. 3894-3908.
  • Holighaus, N.; Koliander, G.; Pruša, Z.; Abreu, L. D. (2019) Non-iterative phaseless reconstruction from wavelet transform magnitude., Proceedings of the DAFx19.
  • Marafioti, A.; Perraudin, N.; Holighaus, N.; Majdak, P. (2019) Adversarial Generation of Time-Frequency Features with application in audio synthesis. In: Chaudhuri, Kamalika; Salakhutdinov, Ruslan (Hrsg.), Proceedings of the 36th International Conference on Machine Learning In Reihe: Proceedings of Machine Learning Research, Bd. 97; Long Beach, California, USA: PMLR, S. 4352-4362.
  • Marafioti, A.; Perraudin, N.; Holighaus, N.; P., Majdak (2019) A context encoder for audio inpainting., Bd. 27 Issue 12, S. 2362 - 2372.
  • Rajbamshi, S.; Balazs, P.; Holighaus, N. (2019) Adhoc method to Invert the Reassigned Time-Frequency Representation., Proceedings of the 23rd International Congress on Acoustics, S. 2789 - 2796.
  • Necciari, T, Holighaus, N.; Balazs, P.; Pruša, Z.; Majdak, P.; Derrien, O. (2018) Audlet Filter Banks: A Versatile Analysis/Synthesis Framework using Auditory Frequency Scales. Applied Sciences, Bd. 8, S. 96-117.
  • Perraudin, N.; Holighaus, N.; Majdak, P.; Balazs, P. (2018) Inpainting of Long Audio Segments with Similarity Graphs. IEEE/ACM Transactions on Audio, Speech, and Language Processing, Bd. 26, S. 1079-1090.
  • Perraudin, N.; Holighaus, N.; Sondergaard, P. L.; Balazs, P. (2018) Designing Gabor windows using convex optimization. Applied Mathematics and Computation, Bd. 330, S. 266 - 287.
  • Holighaus, N.; Wiesmeyr, C.; Balazs, P. (2018) Continuous warped time-frequency representations - Coorbit spaces and discretization. Applied and Computational Harmonic Analysis.
  • Balazs, P.; Holighaus, N.; Necciari, T.; Stoeva, D. T. (2017) Frame Theory for Signal Prcoessing in Psychoacoustics. In: Balan, R.; Benedetto, J. J.; Czaja, W.; Dellatorre, M.; Okoudjou, K. A. (Hrsg.), Excursions in Harmonic Analysis Vol. 5. The February Fourier Talks at the Norbert Wiener Center; Basel: Springer, S. 225-268.
  • Pruša, Z.; Holighaus, N. (2017) Real-Time Audio Visualization With Reassigned Non-uniform Filter Banks., in Proceeding of the 19th International Conference on Digital Audio Effects, DAFx-16; Brno, S. 42950.
  • Pruša, Z.; Holighaus, N. (2017) Phase Vocoder Done Right., Proceedings of 25th European Signal Processing Conference (EUSIPCO-2017); Kos, S. 1006-1010.
  • Pruša, Z.; Holighaus, N. (2017) Non-iterative Filter Bank Phase (Re)Construction., Proceedings of the 25th European Signal Processing Conference (EUSIPCO-2017),; Kos, S. 952-956.
  • Shuman, D. I.; , Wiesmeyr, C.; , Holighaus, N.; , Vandergheynst, P. (2015) Spectrum-adapted tight wavelet and vertex-frequency frames. IEEE Transactions on Signal Processing, Bd. 63, S. 4223 - 4235.
  • Holighaus, N.; C., Wiesmeyr; Balazs, P. (2015) Time-frequency representations for nonlinear frequency scales - Coorbit spaces and discretization., Inproceedings of SampTA 2015.
  • Holighaus, N.; Pruša, Z.; C., Wiesmeyr (2015) Designing tight filter bank frames for nonlinear frequency scales., Inproceedings of SampTA 2015.
  • Schörkhuber, C.; Klapuri, A.; Holighaus, N.; Dörfler, M. (2014) A matlab toolbox for efficient perfect reconstruction time-frequency transforms with log-frequency resolution., Proceedings of the 53rd AES international conference on semantic audio; London, UK, S. CD-ROM.