Lars Thieling, M. Sc.
Scientist
Room: 203
+49 241 80-26959
+49 241 80-22254
thieling(at)iks.rwth-aachen.de
Research
- Machine Learning Assisted Audio Processing
- Reconstruction Of Lost Speech Parts (Speech Inpainting)
Teaching
- Consultant for the study program Computer Engineering (COMP) of Electrical Engineering, Information Technology and Computer Engineering
- Exercise Machine Learning for Speech and Audio Processing
- Laboratory Communications Engineering (experiment 2)
- Laboratory MATLAB meets LEGO Mindstorms
- Seminar Selected Topics in Communications Engineering
Publications
Thieling, L. and Jax, P.: Two-Stage Speech Enhancement Using Gated Convolutions, in Proceedings of International Workshop on Acoustic Signal Enhancement (IWAENC), pp. 1-5, IEEE, Sep. 2022, 10.1109/IWAENC53105.2022.9914693
Thieling, L. and Jax, P.: Generally Applicable Deep Speech Inpainting Using the Example of Bandwidth Extension, in Proceedings of European Signal Processing Conference (EUSIPCO), pp. 451-455, Aug. 2021, 10.23919/EUSIPCO54536.2021.9616099
Thieling, L., Wilhelm, D. and Jax, P.: Recurrent Phase Reconstruction Using Estimated Phase Derivatives From Deep Neural Networks, in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 7088-7092, IEEE, Jun. 2021, 10.1109/ICASSP39728.2021.9413722
Schäfer, M., Thieling, L. and Vollmer, L.: Metrics for the Evaluation of Audio Quality, in Proceedings of German Annual Conference on Acoustics (DAGA), pp. 1390-1393, 2019, ISBN: 978-3-93929-614-0
Liebich, S., Thieling, L., Fabry, J., Jax, P. and Vary, P.: Natural own-voice perception while wearing headphones - Active Occlusion Cancellation with Equalized Hear-Through, in Proceedings of International Workshop on Acoustic Signal Enhancement (IWAENC), IEEE, Sep. 2018