Ein Blick auf: Verstetigung und Transfer im Bundesprogramm „Kita-Einstieg: Brücken bauen in frühe Bildung“ - Albers, Timm; Hoeft, Maike; Abendroth, Sonja; Meusel, Sarah

Erkenntnisse zu Verstetigung und Transfer im Bundesprogramm "Kita-Einstieg: Brücken bauen in frühe Bildung" - Abendroth, Sonja; Hoeft, Maike; Meusel, Sarah

SA-SDR: A Novel Loss Function for Separation of Meeting Style Data - von Neumann, Thilo; Kinoshita, Keisuke; Boeddeker, Christoph; Delcroix, Marc; Haeb-Umbach, Reinhold (ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP))

MMS-MSG: A Multi-purpose Multi-Speaker Mixture Signal Generator - Cord-Landwehr, Tobias; von Neumann, Thilo; Boeddeker, Christoph; Haeb-Umbach, Reinhold (2022 International Workshop on Acoustic Signal Enhancement (IWAENC))
The scope of speech enhancement has changed from a monolithic view of single, independent tasks, to a joint processing of complex conversational speech recordings. Training and evaluation of these single tasks requires synthetic data with access to intermediate signals that is as close as possible to the evaluation scenario. As such data often is not available, many works instead use specialized databases for the training of each system component, e.g WSJ0-mix for source separation. We present a Multi-purpose Multi-Speaker Mixture Signal Generator (MMS-MSG) for generating a variety of speech mixture signals based on any speech corpus, ranging from classical anechoic mixtures (e.g., WSJ0-mix) over reverberant mixtures (e.g., SMS-WSJ) to meeting-style data. Its highly modular and flexible structure allows for the simulation of diverse environments and dynamic mixing, while simultaneously enabling an easy extension and modification to generate new scenarios and mixture types. These meetings can be used for prototyping, evaluation, or training purposes. We provide example evaluation data and baseline results for meetings based on the WSJ corpus. Further, we demonstrate the usefulness for realistic scenarios by using MMS-MSG to provide training data for the LibriCSS database.

Monaural source separation: From anechoic to reverberant environments - Cord-Landwehr, Tobias; Boeddeker, Christoph; von Neumann, Thilo; Zorila, Catalin; Doddipatla, Rama; Haeb-Umbach, Reinhold (2022 International Workshop on Acoustic Signal Enhancement (IWAENC))
Impressive progress in neural network-based single-channel speech source separation has been made in recent years. But those improvements have been mostly reported on anechoic data, a situation that is hardly met in practice. Taking the SepFormer as a starting point, which achieves state-of-the-art performance on anechoic mixtures, we gradually modify it to optimize its performance on reverberant mixtures. Although this leads to a word error rate improvement by 7 percentage points compared to the standard SepFormer implementation, the system ends up with only marginally better performance than a PIT-BLSTM separation system, that is optimized with rather straightforward means. This is surprising and at the same time sobering, challenging the practical usefulness of many improvements reported in recent years for monaural source separation on nonreverberant data.

Rezension von: Viola Schrader: Historisches Denken und sprachliches Handeln. Eine qualitativ-empirische Untersuchung von Schülertexten. Münster et al.: LIT 2021 - Hartung, Olaf (sehepunkte)

On Synchronization of Wireless Acoustic Sensor Networks in the Presence of Time-Varying Sampling Rate Offsets and Speaker Changes - Gburrek, Tobias; Schmalenstroeer, Joerg; Haeb-Umbach, Reinhold (ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP))

Warping of Radar Data Into Camera Image for Cross-Modal Supervision in Automotive Applications - Grimm, Christopher; Fei, Tai; Warsitz, Ernst; Farhoud, Ridha; Breddermann, Tobias; Haeb-Umbach, Reinhold (IEEE Transactions on Vehicular Technology)
We present an approach to automatically generate semantic labels for real recordings of automotive range-Doppler (RD) radar spectra. Such labels are required when training a neural network for object recognition from radar data. The automatic labeling approach rests on the simultaneous recording of camera and lidar data in addition to the radar spectrum. By warping radar spectra into the camera image, state-of-the-art object recognition algorithms can be applied to label relevant objects, such as cars, in the camera image. The warping operation is designed to be fully differentiable, which allows backpropagating the gradient computed on the camera image through the warping operation to the neural network operating on the radar data. As the warping operation relies on accurate scene flow estimation, we further propose a novel scene flow estimation algorithm which exploits information from camera, lidar and radar sensors. The proposed scene flow estimation approach is compared against a state-of-the-art scene flow algorithm, and it outperforms it by approximately 30% w.r.t. mean average error. The feasibility of the overall framework for automatic label generation for RD spectra is verified by evaluating the performance of neural networks trained with the proposed framework for Direction-of-Arrival estimation.

Technically enabled explaining of voice characteristics - Wiechmann, Jana; Glarner, Thomas; Rautenberg, Frederik; Wagner, Petra; Haeb-Umbach, Reinhold (18. Phonetik und Phonologie im deutschsprachigen Raum (P&P))

Long‐term effects of institutional conditions on perceived corruption – A study on organizational imprinting in post‐communist countries - Auer, Thorsten Fabian; Knorr, Karin; Thommes, Kirsten (Business Ethics, the Environment & Responsibility)
In this paper, we apply imprinting theory to examine how institutional transformation substantially influences perceptions of corruption that we argue to be incorporated to a varying extent in organizations founded in that period. For this purpose, we compare the effect of a sudden shock (dissolution of the Soviet Union) on the managers' present perceptions to that of a steady transition (EU accession). We consult the 5th round of the Business Environment and Enterprise Performance Survey from 2012 to 2014 analyzing 4715 interviews with managers of organizations from twelve Central and Eastern European countries. Our results reveal striking differences in the present perception of corruption for organizations founded immediately before and immediately after these institutional transitions. The study's results contribute to the research on imprinting theory regarding the relationship between organizations and institutional conditions that constitutes a lasting effect on organizational structures. Thus, applying an institutional perspective that considers less stable periods for organizations yields a promising avenue in research on organizational behavior.
Keywords: Central and Eastern Europe; corruption; imprinting theory; institutional transformation; shock-imprinting