Dr.-Ing. Anil Nagathil

Ruhr-Universität Bochum
Institut für Kommunikationsakustik
Fakultät für Elektrotechnik und Informationstechnik
Universitätsstr. 150
D-44780 Bochum
Raum: ID/2/319

Email: Anil.Nagathil@rub.de
Tel.: +49 234 32 29289

 

Anil Nagathil studied electrical engineering and information technology at Ruhr-Universität Bochum (RUB) and the University of Birmingham, UK. He obtained the Dipl.-Ing. and Dr.-Ing. degrees from Ruhr-Universität Bochum in 2009 and 2016, respectively. In 2007 he was a research intern at Deutsche Telekom Laboratories, Berlin. Currently, he is a postdoctoral researcher at the Instititute of Communication Acoustics at RUB. His research interests include statistical speech and audio signal processing and machine learning for applications in hearing instruments.



Publications

Book Chapters:

Vatolkin, I., & Nagathil, A. (2019). Evaluation of Audio Feature Groups for the Prediction of Arousal and Valence in Music. In N. Bauer, K. Ickstadt, K. Lübke, G. Szepannek, H. Trautmann, & M. Vichi (Eds.), Studies in Classification, Data Analysis, and Knowledge Organization. Applications in Statistical Computing (Vol. 28, pp. 305–326). Springer International Publishing. (https://doi.org/10.1007/978-3-030-25147-5_19)

Martin R., Nagathil A. (2016). "Digital Filters and Spectral Analysis", in Weihs, C., Jannach, D., Vatolkin, I., Rudolph, G. (eds.): "Music Data Analysis: Foundations and Applications", CRC Press, pp. 111-143, 2016

Nagathil, A., Martin, R. (2016). "Signal-Level Features", in Weihs, C., Jannach, D., Vatolkin, I., Rudolph, G. (eds.): "Music Data Analysis: Foundations and Applications", CRC Press, pp. 145-164, 2016

Journals:

Nagathil, A. & Bruce, I. C. (2023). WaveNet-based approximation of a cochlear filtering and hair cell transduction model. The Journal of the Acoustical Society of America, 154(1), 191–202. https://doi.org/10.1121/10.0020068

Gauer, J., Nagathil, A., Lentz, B., Völter, C. & Martin, R. (2023). A subjective evaluation of different music preprocessing approaches in cochlear implant listeners. The Journal of the Acoustical Society of America, 153(2), 1307-1318. https://doi.org/10.1121/10.0017249

Martin, R., Buyens, W., Nagathil, A., Nogueira, W., van Dijk, B. & Wouters, J. (2023). COMMENT ON "NOVEL WEB-BASED MUSIC RE-ENGINEERING SOFTWARE FOR ENHANCEMENT OF MUSIC ENJOYMENT AMONG COCHLEAR IMPLANTEES" BY HWA ET AL. (OTOL NEUROTOL 2021;42(9). Otology & neurotology, 44 (1), 96–97. https://doi.org/10.1097/MAO.0000000000003752

Gauer, J., Nagathil, A., Eckel, K., Belomestny, D., & Martin, R. (2022). A versatile deep-neural-network-based music preprocessing and remixing scheme for cochlear implant listeners. The Journal of the Acoustical Society of America, 151(5), 2975-2986. (https://doi.org/10.1121/10.0010371)

Gauer, J., Nagathil, A., Martin, R., Thomas, J. P., & Völter, C. (2019). Interactive Evaluation of a Music Preprocessing Scheme for Cochlear Implants Based on Spectral Complexity Reduction. Frontiers in Neuroscience, 13, 1206. (https://doi.org/10.3389/fnins.2019.01206)

Nogueira, W., Nagathil, A., Martin, R. (2019). "Making Music More Accessible for Cochlear Implant Listeners: Recent Developments", IEEE Signal Processing Magazine, vol. 36, no. 1, pp. 115-127, January 2019.

Nagathil, A., Schlattmann, J.-W., Neumann, K., Martin, R. (2018). "Music Complexity Prediction for Cochlear Implant Listeners Based on a Feature-based Linear Regression Model", J. Acous. Soc. Am. (JASA), 144(1), pp. 1-10, July 2018.

Nagathil, A., Weihs, C., Neumann, K., Martin, R. (2017). "Spectral Complexity Reduction of Music Signals Based on Frequency-domain Reduced-rank Approximations: An Evaluation with Cochlear Implant Listeners," J. Acous. Soc. Am. (JASA), 142(3), pp. 1219-1228, September 2017.

Nagathil, A., Weihs, C., Martin, R. (2016). “Spectral Complexity Reduction of Music Signals for Mitigating Effects of Cochlear Hearing Loss,” IEEE/ACM Trans. Audio, Speech, and Language Processing, vol. 24, no. 3, pp. 445-458, March 2016.

Gergen, S., Nagathil, A., Martin, R. (2015). "Classification of reverberant audio signals using clustered ad hoc distributed microphones". Signal Processing, 107, pp. 21-32, February 2015

Conference Proceedings (peer-reviewed):

Nagathil, A., Göbel, F., Nelus, A., Bruce, I.C. (2021). “Computationally Efficient DNN-based Approximation of an Auditory Model for Applications in Speech Processing,” in Proc. International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Toronto, Canada, June 2021

Lentz, B., Nagathil, A., Gauer, J., Martin, R. (2020). “Harmonic/Percussive Sound Separation and Spectral Complexity Reduction of Music Signals for Cochlear Implant Listeners”, in Proc. International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 8713-8717, Barcelona, Spain, May 2020 (Virtual Conference)

Nagathil, A., Martin, R. (2019). "Objective Evaluation of Ideal Time-Frequency Masking for Music Complexity Reduction in Cochlear Implants," in Proc. International Symposium on Computer Music Multidisciplinary Research (CMMR), Marseille, France.

Lentz, B., Nagathil, A., Gauer, J., and Martin, R. (2019). “Music Simplification for Cochlear Implant Users through Harmonic/Percussive Sound Separation and Spectral Complexity Reduction,” In: 22. Jahrestagung Der Deutschen Gesellschaft Für Audiologie, p. 1 (Abstract).

Gauer, J., Nagathil, A., Martin, R. (2018). "Binaural spectral complexity reduction of music signals for cochlear implant listeners", in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Canada, April 2018.

Nagathil, A., Schlattmann, J.-W., Neumann, K., Martin, R. (2017). "A Feature-based Linear Regression Model for Predicting Perceptual Ratings of Music by Cochlear Implant Listeners," in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), New Orleans, USA, March 2017.

Krymova, E., Nagathil, A., Belomestny, D., Martin, R. (2017). "Segmentation of Music Signals Based on Explained Variance Ratio for Applications in Spectral Complexity Reduction," in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), New Orleans, USA, March 2017.

Gergen, S., Nagathil, A., Martin, R. (2015). "Reduction of reverberation effects in the MFCC modulation spectrum for improved classification of acoustic signals", Interspeech 2015, Dresden, September 2015.

Nagathil, A., Martin, R. (2013). "Evaluation of Spectral Transforms for Music Signal Analysis," in Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), New Paltz, New York, USA, October 2013.

Gergen, S., Nagathil, A., Martin, R. (2013). "Audio Signal Classification in Reverberant Environments Based on Fuzzy-Clustered Ad-hoc Microphone Arrays", International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2013, Vancouver, Canada, May 2013.

Vatolkin I., Nagathil A., Theimer W., Martin R. (2013). “Performance of Specific vs. Generic Feature Sets in Polyphonic Music Instrument Recognition,” in Proc. 7th Int. Conf. on Evolutionary Multi-Criterion Optimization (EMO), Sheffield, UK, March 2013.

Nagathil, A., Martin, R. (2012). "Optimal Signal Reconstruction from a Constant-Q Spectrum", ICASSP, pp. 349-352, Kyoto, Japan, March 2012.

Nagathil, A., Göttel, P., Martin, R. (2011). “Hierarchical Audio Classification Using Cepstral Modulation Ratio Regressions Based on Legendre Polynomials,” in Proc. International Conference on Acoustics, Speech and Signal Processing (ICASSP), Prague, Czech Republic, May 2011

Nagathil, A., Vatolkin, I., Theimer, W. (2010). “Comparison of Partition-Based Audio Features for Music Classification,” in Proc. 9. ITG-Fachtagung Sprachkommunikation, Bochum, Germany, October 2010

Nagathil, A., Gerkmann, T., Martin, R. (2010). “Musical Genre Classification Based on a Highly-resolved Cepstral Modulation Spectrum,” in Proc. European Signal Processing Conference (EUSIPCO), Aalborg, Denmark, August 2010

Martin, R., Nagathil, A. (2009). “Cepstral Modulation Ratio Regression (CMRARE) Parameters for Audio Signal Analysis and Classification,” in Proc. International Conference on Acoustics, Speech and Signal Processing (ICASSP), Taipei, Taiwan, April 2009

Mauler, D., Nagathil, A., Martin, R. (2007). "On Optimal Estimation of Compressed Speech for Hearing Aids," in Proc. Interspeech, Antwerp, Belgium, August 2007

Other Conference Proceedings:

Neudek, D., Nagathil, A., Wißmann, A., Getzmann, S., Martin, R. (2021). "On Least-squares-based Auditory Attention Decoding with Individual Neural Latency Compensation", in Proc. Deutsche Jahrestagung für Akustik (DAGA), 2021.

Neudek, D., Nagathil, A., Getzmann, S., Martin, R. (2020). "Speaker Change Detection Based on Event-Related Potentials with a Consumer Brain-Computer Interface", in Proc. Deutsche Jahrestagung für Akustik (DAGA), 2020

Gauer, J., Nagathil, A., Martin, R., Thomas J.-P., Völter, C. (2018). "Validation of a Music Enhancement Method for CI Listeners Using an Interactive User Interface", (Extended Abstract) Proc. International Workshop on Speech Processing for Voice, Speech, and Hearing Disorders, Mysore, India, Sept. 8-9, 2018.

Nagathil, A., Weihs C., Martin R. (2015). “Signal Processing Strategies for Improving Music Perception in the Presence of a Cochlear Hearing Loss,” in Proc. Jahrestagung der Deutschen Gesellschaft für Audiologie (DGA), Bochum, Germany, ISBN 978-3-9813141-5-1.

Nagathil, A., Gerkmann, T., Martin, R. (2010). “Cepstral Modulation Features for Classifying Audio Data,” in Proc. 36. Deutsche Jahrestagung für Akustik (DAGA), Berlin, Germany, March 2010

Abstracts and Talks/Poster:

Nagathil, A., Gauer, J., Jeyachandran, S., Martin, R. (2023). "Individualized optimization of a music remixing method for cochlear implant users," Conference on Implantable Auditory Prostheses (CIAP), Lake Tahoe, USA, July 2023

Nagathil, A., Bruce, I.C. (2023). "A WaveNet-based cochlear filtering and hair cell transduction model for applications in speech and music processing," 4th Virtual Conference on Computational Audiology (VCCA), June 2023.

Nagathil, A., Bruce, I.C. (2022). “A Deep-learning-based Approximation of a Cochlear Filtering Auditory Model for Applications in Speech and Music Processing,” Music and Hearing Health Workshop, Oldenburg, Germany, October 2022

Nagathil, A., Schlattmann, J.-W., Neumann, K., Martin, R. (2017). “Evaluation of Spectral Music Complexity Reduction Methods for Cochlear Implant Listeners by Means of a Perceptual Music Quality Prediction Model”, Conference on Implantable Auditory Prostheses (CIAP), Lake Tahoe, USA,  July 2017

Nagathil, A., Weihs C., Neumann, K., Martin, R. (2016). “Frequency-domain Reduced-rank Approximations of Music Signals for the Improvement of Music Perception in Cochlear Implant Listeners,” ARCHES Meeting/ICanHear Conference, Zurich, Switzerland, 21.-23. November 2016

Nagathil, A., Martin, R. (2014). “Investigation into Properties of Spectral Transforms with Respect to Music Signal Analysis,” Erlanger Kolloquium, Erlangen, Germany, 28. Februar 2014

Nagathil, A., Martin, R. (2012). “Towards Timbre-controlled Reconstruction of Music Signals in the CQT Domain,“ 11th Workshop on Quality Improvement Methods, Dortmund, Germany, 8. Juni 2012

Nagathil, A., Martin, R. (2011). ”Cepstral Modulation Features for Versatile Audio Classification Tasks,” Joint Annual Conference of the German Association for Pattern Recognition (DAGM) and the German Classification Society (GfKL), Franfurt, Germany, 1. September 2011

Nagathil, A., Martin, R. (2010). ”Statistical Properties of Cepstral Modulation Features for Audio Signal Analysis,” 2nd Joint Statistical Meeting Deutsche Arbeitsgemeinschaft Statistik (DAGStat), Dortmund, Germany, March 2010

 

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