@article{48432,
  author       = {{Wille, Manuel}},
  journal      = {{Wörterbücher zur Sprach- und Kommunikationswissenschaft (WSK) Online, edited by Stefan J. Schierholz.}},
  publisher    = {{Berlin, Boston: De Gruyter}},
  title        = {{{Pressesprache}}},
  year         = {{2020}},
}

@article{48431,
  author       = {{Wille, Manuel}},
  journal      = {{Wörterbücher zur Sprach- und Kommunikationswissenschaft (WSK) Online, edited by Stefan J. Schierholz.}},
  publisher    = {{ Berlin, Boston: De Gruyter}},
  title        = {{{Zeitungsstil}}},
  year         = {{2020}},
}

@article{48466,
  author       = {{Jacke, Christoph}},
  journal      = {{Die Aufhebung}},
  title        = {{{So Far...From Now On # 6. }}},
  year         = {{2020}},
}

@inproceedings{20505,
  abstract     = {{Speech activity detection (SAD), which often rests on the fact that the noise is "more'' stationary than speech, is particularly challenging in non-stationary environments, because the time variance of the acoustic scene makes it difficult to discriminate  speech from noise. We propose two approaches to SAD, where one is based on statistical signal processing, while the other utilizes neural networks. The former employs sophisticated signal processing to track the noise and speech energies and is meant to support the case for a resource efficient, unsupervised signal processing approach.
The latter introduces a recurrent network layer that operates on short segments of the input speech to do temporal smoothing in the presence of non-stationary noise. The systems are tested on the Fearless Steps challenge database, which consists of the transmission data from the Apollo-11 space mission.
The statistical SAD  achieves comparable detection performance to earlier proposed neural network based SADs, while the neural network based approach leads to a decision cost function of 1.07% on the evaluation set of the 2020 Fearless Steps Challenge, which sets a new state of the art.}},
  author       = {{Heitkaemper, Jens and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}},
  booktitle    = {{INTERSPEECH 2020 Virtual Shanghai China}},
  keywords     = {{voice activity detection, speech activity detection, neural network, statistical speech processing}},
  title        = {{{Statistical and Neural Network Based Speech Activity Detection in Non-Stationary Acoustic Environments}}},
  year         = {{2020}},
}

@article{48524,
  author       = {{Hubner-Benz, Sylvia}},
  issn         = {{1742-5360}},
  journal      = {{International Journal of Entrepreneurial Venturing}},
  keywords     = {{Management of Technology and Innovation, Strategy and Management, Business and International Management}},
  number       = {{2}},
  publisher    = {{Inderscience Publishers}},
  title        = {{{When entrepreneurs become leaders: how entrepreneurs deal with people management}}},
  doi          = {{10.1504/ijev.2020.105571}},
  volume       = {{12}},
  year         = {{2020}},
}

@article{48521,
  author       = {{Rudic, Biljana and Hubner-Benz, Sylvia and Baum, Matthias}},
  issn         = {{2352-6734}},
  journal      = {{Journal of Business Venturing Insights}},
  keywords     = {{Management of Technology and Innovation, Business and International Management}},
  publisher    = {{Elsevier BV}},
  title        = {{{Hustlers, hipsters and hackers: Potential employees’ stereotypes of entrepreneurial leaders}}},
  doi          = {{10.1016/j.jbvi.2020.e00220}},
  volume       = {{15}},
  year         = {{2020}},
}

@article{48523,
  author       = {{Gales, Alina and Hubner-Benz, Sylvia}},
  issn         = {{1664-1078}},
  journal      = {{Frontiers in Psychology}},
  keywords     = {{General Psychology}},
  publisher    = {{Frontiers Media SA}},
  title        = {{{Perceptions of the Self Versus One’s Own Social Group: (Mis)conceptions of Older Women’s Interest in and Competence With Technology}}},
  doi          = {{10.3389/fpsyg.2020.00848}},
  volume       = {{11}},
  year         = {{2020}},
}

@article{47919,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>We examine whether and how political embeddedness influences financial reporting quality in China by investigating how government ownership and political connections affect Chinese listed firms’ choices of earnings management strategies. The results show that state‐owned enterprises (SOEs), and in particular, central SOEs, are more likely to substitute accrual‐based earnings management strategies with costlier but less detectable real earnings management strategies than non‐SOEs. The results also indicate that politically connected enterprises (PCEs) are more likely to employ less detectable real earnings management strategies than non‐PCEs, so much so that PCEs’ total earnings management level is higher than that of non‐PCEs.</jats:p>}},
  author       = {{Wang, Zhi and Braam, Geert and Reimsbach, Daniel and Wang, Jiaxin}},
  issn         = {{0810-5391}},
  journal      = {{Accounting &amp; Finance}},
  keywords     = {{Economics, Econometrics and Finance (miscellaneous), Finance, Accounting}},
  number       = {{5}},
  pages        = {{4723--4755}},
  publisher    = {{Wiley}},
  title        = {{{Political embeddedness and firms’ choices of earnings management strategies in China}}},
  doi          = {{10.1111/acfi.12690}},
  volume       = {{60}},
  year         = {{2020}},
}

@article{47918,
  author       = {{Hahn, Rüdiger and Reimsbach, Daniel}},
  issn         = {{2168-1007}},
  journal      = {{Academy of Management Discoveries}},
  number       = {{1}},
  pages        = {{155--157}},
  publisher    = {{Academy of Management}},
  title        = {{{Bringing Signaling Theory to Intermediated Voluntary Disclosure. Commentary on “Detecting False Accounts in Intermediated Voluntary Disclosure” by Patrick Callery and Jessica Perkins}}},
  doi          = {{10.5465/amd.2020.0015}},
  volume       = {{7}},
  year         = {{2020}},
}

@article{45383,
  author       = {{Dröse, Jennifer and Prediger, Susanne}},
  journal      = {{Journal für Mathematik-Didaktik, 41(2)}},
  pages        = {{399--422}},
  title        = {{{Enhancing Fifth Graders’ Awareness of Syntactic Features in Mathematical Word Problems: A Design Research Study on the Variation Principle}}},
  doi          = {{doi.org/10.1007/s13138-019-00153-z}},
  year         = {{2020}},
}

@inbook{29413,
  author       = {{Flaßkamp, K. and Ober-Blöbaum, Sina and Peitz, S. }},
  booktitle    = {{Advances in Dynamics, Optimization and Computation}},
  editor       = {{Junge, Oliver and Schütze, Oliver and Froyland, Gary and Ober-Blöbaum, Sina and Padberg-Gehle, Kathrin}},
  pages        = {{209--237}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Symmetry in optimal control: A multiobjective model predictive control approach}}},
  year         = {{2020}},
}

@inbook{48690,
  author       = {{Spener, Anna Maria}},
  booktitle    = {{Celan-Jahrbuch 11}},
  editor       = {{Speier, Hans-Michael}},
  pages        = {{301–327}},
  publisher    = {{Königshausen & Neumann}},
  title        = {{{"Dein jüdisches Gesicht". Zu drei Gedichten des "Ilana"-Zyklus von Paul Celan}}},
  year         = {{2020}},
}

@inbook{48723,
  author       = {{Krause, Daniel and Blischke, Klaus}},
  booktitle    = {{Bewegung, Training, Leistung und Gesundheit}},
  editor       = {{Güllich, Arne and Krüger, Michael}},
  publisher    = {{Springer}},
  title        = {{{Automatisierung der motorischen Kontrolle}}},
  doi          = {{doi.org/10.1007/978-3-662-53386-4_62-1}},
  year         = {{2020}},
}

@article{48382,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>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.</jats:p>}},
  author       = {{Schnettler, Theresa and Bobe, Julia and Scheunemann, Anne and Fries, Stefan and Grunschel, Carola}},
  issn         = {{0146-7239}},
  journal      = {{Motivation and Emotion}},
  keywords     = {{Experimental and Cognitive Psychology, Social Psychology}},
  number       = {{4}},
  pages        = {{491--507}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Is it still worth it? Applying expectancy-value theory to investigate the intraindividual motivational process of forming intentions to drop out from university}}},
  doi          = {{10.1007/s11031-020-09822-w}},
  volume       = {{44}},
  year         = {{2020}},
}

@inproceedings{20762,
  abstract     = {{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.}},
  author       = {{von Neumann, Thilo and Kinoshita, Keisuke and Drude, Lukas and Boeddeker, Christoph and Delcroix, Marc and Nakatani, Tomohiro and Haeb-Umbach, Reinhold}},
  booktitle    = {{ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}},
  pages        = {{7004--7008}},
  title        = {{{End-to-End Training of Time Domain Audio Separation and Recognition}}},
  doi          = {{10.1109/ICASSP40776.2020.9053461}},
  year         = {{2020}},
}

@inproceedings{20764,
  abstract     = {{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. }},
  author       = {{von Neumann, Thilo and Boeddeker, Christoph and Drude, Lukas and Kinoshita, Keisuke and Delcroix, Marc and Nakatani, Tomohiro and Haeb-Umbach, Reinhold}},
  booktitle    = {{Proc. Interspeech 2020}},
  pages        = {{3097--3101}},
  title        = {{{Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR}}},
  doi          = {{10.21437/Interspeech.2020-2519}},
  year         = {{2020}},
}

@article{48615,
  author       = {{Hartung, Olaf}},
  issn         = {{1434-9736}},
  journal      = {{Paderborner Universitätszeitschrift}},
  pages        = {{88}},
  publisher    = {{Uni8versität paderborn}},
  title        = {{{Workshops zur geschichtsdidaktischen Lehre in Zeiten von Corona}}},
  volume       = {{2}},
  year         = {{2020}},
}

@inproceedings{18651,
  abstract     = {{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. }},
  author       = {{Gburrek, Tobias and Schmalenstroeer, Joerg and Brendel, Andreas and Kellermann, Walter and Haeb-Umbach, Reinhold}},
  booktitle    = {{European Signal Processing Conference (EUSIPCO)}},
  title        = {{{Deep Neural Network based Distance Estimation for Geometry Calibration in Acoustic Sensor Network}}},
  year         = {{2020}},
}

@article{49094,
  author       = {{Krebs, Benjamin and Kabst, Rüdiger}},
  journal      = {{PERSONALquartely}},
  title        = {{{Corporate Entrepreneurship: Die Rolle und Bedeutung des Humankapitals}}},
  volume       = {{4}},
  year         = {{2020}},
}

@inbook{49102,
  author       = {{Megow, N. and Kabst, Rüdiger}},
  booktitle    = {{Perspektiven des Entrepreneurships: Unternehmerische Konzepte zwischen Theorie und Praxis}},
  editor       = {{Hölzle, K. and Tiberius, V. and Surrey, H.}},
  pages        = {{251--262}},
  title        = {{{Corporate Entrepreneurship durch die Allokation von Ressourcen}}},
  year         = {{2020}},
}