Kommunikationstechnik-Kolloquium January 2023

kommunikationstechnik-kolloquium@lists.rwth-aachen.de

1 participants
2 discussions

Communication Technology Collquium at IKS

by Irina Esser

Dear subscribers of the Colloquium Newsletter, we are happy to inform you about the next date of our Communication Technology Colloquium. *Wednesday, 30. November 2022** **Speaker:* Frederick Pietschmann *Time*: 14:00 *Location:* Lecture room 4G and https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09 Meeting-ID: 979 0415 7921 Passwort: 481650 *Master-Lecture*: Perceptual Optimization and Evaluation of a Binaural Signal Modification Algorithm With individualized binaural signals, it is possible to reproduce auditory scenes such that the signal is perceived similar to the real scene. However, perceptual similarity is no longer achieved when the binaural signal doesn’t fully adapt to diﬀerent listeners and diﬀerent orientations of the listener’s head. To address these problems, a perceptually motivated algorithm referred to as the Binaural Cue Adaptation (BCA) system has been developed at the Institute of Communication Systems. The BCA system is capable of adding both interactivity and individualization to existing binaural signals, thereby achieving a higher degree of perceptual similarity to a corresponding real auditory scene. In this thesis, a perceptual optimization of the existing BCA system is conducted in that new approaches for some components of the algorithm are proposed, all parametrization options are identiﬁed and the overall best parametrization is chosen. To identify the best parametrization, both an isolated analysis of individual components is conducted and a perceptually motivated optimization procedure for a full system analysis is proposed and implemented. Finally, a perceptual evaluation based on the result of the perceptual optimization is realized. For this, two listening tests with a total number of 17 participants are conducted – one for a normal and one for a highly reverberant scenario. The results of these listening tests suggest that signals produced by the optimized BCA system achieve a high degree of perceptual plausibility for both reverberation scenarios, with an averaged 2AFC probability to detect a BCA-generated signal of 0.563 for the normal scenario and 0.604 for the highly reverberant scenario. All interested parties are cordially invited, registration is not required. General information on the colloquium, as well as a current list of dates of the Communication Technology Colloquium can be fount at: https://www.iks.rwth-aachen.de/aktuelles/kolloquium -- Irina Esser Institute of Communication Systems (IKS) RWTH Aachen University Muffeter Weg 3a, 52074 Aachen, Germany +49 241 80 26958 (phone) esser(a)iks.rwth-aachen.de http://www.iks.rwth-aachen.de/

3 months, 2 weeks

Communication Technology Colloquium at IKS

by Simone Sedgwick

Dear subscribers of the colloquium newsletter, we are happy to inform you about the next date of our Communication Technology Colloquium. *Wednesday, January 18, 2022* *Speaker*: Konstantin Wehmeyer *Time:* 2:00 p.m. *Location*: hybrid - Lecture room 4G and https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09 Meeting-ID: 979 0415 7921 Passwort: 481650 *Bachelor-Lecture: ***Deep Learning-Based Speech Synthesis as Post-Processing of a Noise Reduction /Audio and speech signals are often disturbed by noise signals in frequency- and/or time-limited parts. To attenuate or remove these distortions, several methods, including deep learning- based approaches, are known. Often, however, only the magnitude spectrum is processed and the phase spectrum is taken over unchanged due to its comparatively lower relevance. Consequently, the noisy phase is reused when synthesizing the waveform from the processed magnitude spectrum. Therefore, distortions in the magnitude spectrum can be reduced, but not in the phase spectrum which inevitably leads to a deterioration in speech quality and intelligibility./ /This thesis presents methods that allow a reconstruction of the phase spectrum of speech signals based on noise-reduced magnitude spectra. At the Institute of Communication Systems at RWTH Aachen University a phase reconstruction algorithm was developed and this algorithm has already been evaluated in a previous study for the case of smoothed magnitude spectra. It was shown that the deep neural network (DNN) used can benefit from targeted training on the smoothed magnitude spectra even without further modification of the network structures. However, even slight smearing of the magnitude spectra already leads to a significant loss in performance compared to the use of perfect magnitude spectra. In this work, therefore, the DNNs used are optimized for the case of noise-reduced magnitude spectra. // / /Several deep learning-based models are introduced and compared with each other and with the models already developed. Their properties and aspects such as causality are addressed. Moreover, a new loss function and assessment measure specifically designed to estimate and assess the phase spectrum of speech signals is developed and tested. In order to be able to evaluate the results as independently as possible of a specific type of noise reduction, ideal masks are developed, used, and discussed. / All interested parties are cordially invited, registration is not required. General information on the colloquium, as well as a current list of dates of the Communication Technology Colloquium can be found at: https://www.iks.rwth-aachen.de/aktuelles/kolloquium -- Simone Sedgwick Institute of Communication Systems(IKS) Prof. Dr.-Ing. Peter Jax RWTH Aachen University Muffeter Weg 3a, 52074 Aachen, Germany +49 241 80 26956(phone) +49 241 80 22254(fax) sedgwick(a)iks.rwth-aachen.de https://www.iks.rwth-aachen.de/

5 months, 1 week

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Kommunikationstechnik-Kolloquium January 2023