"Dein jüdisches Gesicht". Zu drei Gedichten des "Ilana"-Zyklus von Paul Celan - Spener, Anna Maria (Celan-Jahrbuch 11)

Automatisierung der motorischen Kontrolle - Krause, Daniel; Blischke, Klaus (Bewegung, Training, Leistung und Gesundheit)

Is it still worth it? Applying expectancy-value theory to investigate the intraindividual motivational process of forming intentions to drop out from university - Schnettler, Theresa; Bobe, Julia; Scheunemann, Anne; Fries, Stefan; Grunschel, Carola (Motivation and Emotion)
Abstract The intraindividual process of study dropout, from forming dropout intention to deregistration, is of motivational nature. Yet typical studies investigate interindividual differences, which do not inform about intraindividual processes. Our study focused on the intraindividual process of forming dropout intention, and applied expectancy-value theory to analyze its motivational underpinnings. To expand research, we considered associations of intraindividual deviations in expectancy, intrinsic value, attainment value, utility value, and cost to intraindividual deviations in dropout intention. A total of 326 undergraduate students of law and mathematics rated motivational variables and dropout intention three times from semester start to the final exam period. Multilevel regression analyses revealed that intraindividual changes in intrinsic value, attainment, and cost, but not in expectancy and utility, related to intraindividual changes in dropout intention. Further, we considered students’ demographics as moderators. Only age moderated the association between intrinsic value and dropout intention. Our results stress the crucial role of certain value components, including cost, for emerging dropout intention.
Keywords: Experimental and Cognitive Psychology; Social Psychology

End-to-End Training of Time Domain Audio Separation and Recognition - von Neumann, Thilo; Kinoshita, Keisuke; Drude, Lukas; Boeddeker, Christoph; Delcroix, Marc; Nakatani, Tomohiro; Haeb-Umbach, Reinhold (ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP))
The rising interest in single-channel multi-speaker speech separation sparked development of End-to-End (E2E) approaches to multispeaker speech recognition. However, up until now, state-of-theart neural network–based time domain source separation has not yet been combined with E2E speech recognition. We here demonstrate how to combine a separation module based on a Convolutional Time domain Audio Separation Network (Conv-TasNet) with an E2E speech recognizer and how to train such a model jointly by distributing it over multiple GPUs or by approximating truncated back-propagation for the convolutional front-end. To put this work into perspective and illustrate the complexity of the design space, we provide a compact overview of single-channel multi-speaker recognition systems. Our experiments show a word error rate of 11.0% on WSJ0-2mix and indicate that our joint time domain model can yield substantial improvements over cascade DNN-HMM and monolithic E2E frequency domain systems proposed so far.

Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR - von Neumann, Thilo; Boeddeker, Christoph; Drude, Lukas; Kinoshita, Keisuke; Delcroix, Marc; Nakatani, Tomohiro; Haeb-Umbach, Reinhold (Proc. Interspeech 2020)
Most approaches to multi-talker overlapped speech separation and recognition assume that the number of simultaneously active speakers is given, but in realistic situations, it is typically unknown. To cope with this, we extend an iterative speech extraction system with mechanisms to count the number of sources and combine it with a single-talker speech recognizer to form the first end-to-end multi-talker automatic speech recognition system for an unknown number of active speakers. Our experiments show very promising performance in counting accuracy, source separation and speech recognition on simulated clean mixtures from WSJ0-2mix and WSJ0-3mix. Among others, we set a new state-of-the-art word error rate on the WSJ0-2mix database. Furthermore, our system generalizes well to a larger number of speakers than it ever saw during training, as shown in experiments with the WSJ0-4mix database.

Gedenken an Luftangriffe auf Paderborn: "Erinnerung wird nie obsolet sein" - Hartung, Olaf (Neue Westfälische)

Workshops zur geschichtsdidaktischen Lehre in Zeiten von Corona - Hartung, Olaf (Paderborner Universitätszeitschrift)

Deep Neural Network based Distance Estimation for Geometry Calibration in Acoustic Sensor Network - Gburrek, Tobias; Schmalenstroeer, Joerg; Brendel, Andreas; Kellermann, Walter; Haeb-Umbach, Reinhold (European Signal Processing Conference (EUSIPCO))
We present an approach to deep neural network based (DNN-based) distance estimation in reverberant rooms for supporting geometry calibration tasks in wireless acoustic sensor networks. Signal diffuseness information from acoustic signals is aggregated via the coherent-to-diffuse power ratio to obtain a distance-related feature, which is mapped to a source-to-microphone distance estimate by means of a DNN. This information is then combined with direction-of-arrival estimates from compact microphone arrays to infer the geometry of the sensor network. Unlike many other approaches to geometry calibration, the proposed scheme does only require that the sampling clocks of the sensor nodes are roughly synchronized. In simulations we show that the proposed DNN-based distance estimator generalizes to unseen acoustic environments and that precise estimates of the sensor node positions are obtained.

Corporate Entrepreneurship: Die Rolle und Bedeutung des Humankapitals - Krebs, Benjamin; Kabst, Rüdiger (PERSONALquartely)

Corporate Entrepreneurship durch die Allokation von Ressourcen - Megow, N.; Kabst, Rüdiger (Perspektiven des Entrepreneurships: Unternehmerische Konzepte zwischen Theorie und Praxis)