Patents

• Schädler, M. R. et al. "SCHNELLE ADAPTIVE DYNAMIKKOMPRESSION", German Patent 10 2017 216 972.9 (filed 2017-09-25)

Publications

Journal articles

• Schädler, M. R., Hülsmeier, D., Warzybok, A., and Kollmeier, B. "Individual Aided Speech-Recognition Performance and Predictions of Benefit for Listeners With Impaired Hearing Employing FADE", Trends in Hearing, Volume 24 (2020). [link]
   
• Siedenburg K, Schädler MR, Hülsmeier D (2019) Modeling the onset advantage in musicalinstrument recognition. J Acoust Soc Am 146 (6): EL523 - EL529. [link]
   
• Schädler, M. R., Warzybok, A., and Kollmeier, B., "Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms", Trends in Hearing, Volume 22 (2018). [link]
   
• Kollmeier, B., Schädler, M. R., Warzybok, A., Meyer, B., and Brand, T., "Sentence recognition prediction for hearing-impaired listeners in stationary and fluctuation noise with FADE: Empowering the Attenuation and Distortion concept by Plomp with a quantitative processing model", Trends in Hearing, Volume 20 (2016). [link]
   
• Schädler, M. R., Warzybok, A., Ewert, S. D., and Kollmeier, B., "A simulation framework for auditory discrimination experiments: Revealing the importance of across-frequency processing in speech perception", Journal of the Acoustical Society of America, Volume 139, Issue 5, pp. 2708–2723 (2016). [link|pdf¹]
   
• Schädler, M. R., Warzybok, A., Hochmuth, S., and Kollmeier, B., "Matrix sentence intelligibility prediction using an automatic speech recognition system", International Journal of Audiology, Volume 54, Issue Supplement 2, pp 100–107 (2015). [link]
   
• Schädler, M. R. and Kollmeier, B., "Separable spectro-temporal Gabor filter bank features: Reducing the complexity of robust features for automatic speech recognition", Journal of the Acoustical Society of America, Volume 137, Issue 4, pp 2047-2059 (2015). [link|pdf¹]
   
• Schädler, M. R., Meyer, B. T., and Kollmeier, B., "Spectro-temporal modulation subspace-spanning filter bank features for robust automatic speech recognition", Journal of the Acoustical Society of America, Volume 131, Issue 5, pp 4134-4151 (2012). [link|pdf¹]

1) Copyright (2012, and 2015) Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America.

Peer-reviewed conference proceedings

• Schädler MR (2020) Optimization and evaluation of an intelligibility-improving signal pProcessing approach (IISPA) for the Hurricane Challenge 2.0 with FADE. Proc. Interspeech 2020, 1331-1335, [link]
   
• Martinez, A. M. C., and Schädler, M. R., "Why do ASR Systems Despite Neural Nets Still Depend on Robust Features", in Proceeding of INTERSPEECH (2016).
   
• Schädler, M. R., Hülsmeier, D., Warzybok, A., Hochmuth, S., and Kollmeier, B., "Microscopic Multilingual Matrix Test Predictions Using an ASR-Based Speech Recognition Model.", in Proceeding of INTERSPEECH (2016).
   
• Schädler, M.R., and Kollmeier, B., "Normalization of spectro-temporal Gabor filter bank features for improved robust automatic speech recognition systems", in Proceeding of INTERSPEECH (2012). [pdf]
   
• Kollmeier, B., Schädler, M.R., Meyer, A., Anemüller, J., and Meyer, B., "Do we need STRFs for cocktail parties? - On the relevance of physiologically motivated features for human speech perception derived from automatic speech recognition", in Proceeding of the International Symposium of Hearing (ISH), Cambridge, UK (2012).

Open-source software/hardware projects

• "Reference Matlab/Octave implementations of feature extraction algorithms" [GitHub]
   
• "Simulation Framework for auditory discrimination experiments" (FADE) on [GitHub]
   
• "Instructions for building an almost consumer hardware based prototype of a hearing aid" [GitHub]