Senior Research Associate
Mathematics and Signal Processing in Acoustics
Machine Learning

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

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

 

Academic Background


Nicki Holighaus studied mathematics and theoretical computer sciences at Justus–Liebig–University, Gießen, Germany. He graduated in 2010. After three years of doctoral studies at the University of Vienna, Austria, where he worked as a research assistant at the Numerical Harmonic Analysis Group (NuHAG), he successfully defended his PhD thesis "Theory and implementation of adaptive time-frequency transforms” in October 2013.

Since August 2012 he is part of the Acoustic Research Institute's workgroup "Mathematics and Signal Processing in Acoustics", where he works on theoretical and applied aspects of frames and adapted time-frequency representations. 

Current Research


His research focuses on advanced time-frequency methods in signal processing, including time-frequency analysis, the mathematical theory and design of adaptive and adapted time-frequency representations, time-frequency processing in acoustics and the use of time-frequency representations in machine learning for acoustics.  

Current research projects: MERLIN

Current topics:

  • 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

Publications

Publications

  • 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.