The inverse perovskite BaLiF3: single-crystal neutron diffraction and analyses of potential ion pathways

Doped barium lithium trifluoride has attracted attention as component for scintillators, luminescent materials and electrodes. With lithium and fluoride, it contains two possibly mobile species, which may account for its ionic conductivity. In this study, neutron diffraction on oxide-containing BaLiF3 single-crystals is performed at up to 636.2°C. Unfortunately, ion-migration pathways could not be mapped by modelling anharmonic ion displacement or by inspecting the scattering-length density that was reconstructed via maximum-entropy methods. However, analyses of the topology and bond-valence site energies derived from the high-temperature structure reveal that the anions can migrate roughly along the edges of the LiF6 coordination octahedra with an estimated migration barrier of ∼0.64 eV (if a vacancy permits), whereas the lithium ions are confined to their crystallographic positions. This finding is not only valid for the title compound but for ion migration in all perovskites with Goldschmidt tolerance factors near unity

Improving audio-visual speech recognition using deep neural networks with dynamic stream reliability estimates

Audio-visual speech recognition is a promising approach to tackling the problem of reduced recognition rates under adverse acoustic conditions. However, finding an optimal mechanism for combining multi-modal information remains a challenging task. Various methods are applicable for integrating acoustic and visual information in Gaussian-mixture-model-based speech recognition, e.g., via dynamic stream weighting. The recent advances of deep neural network (DNN)-based speech recognition promise improved performance when using audio-visual information. However, the question of how to optimally integrate acoustic and visual information remains. In this paper, we propose a state-based integration scheme that uses dynamic stream weights in DNN-based audio-visual speech recognition. The dynamic weights are obtained from a time-variant reliability estimate that is derived from the audio signal. We show that this state-based integration is superior to early integration of multi-modal features, even if early integration also includes the proposed reliability estimate. Furthermore, the proposed adaptive mechanism is able to outperform a fixed weighting approach that exploits oracle knowledge of the true signal-to-noise ratio

The Aluminum-Ion Battery: A Sustainable and Seminal Concept?

The expansion of renewable energy and the growing number of electric vehicles and mobile devices are demanding improved and low-cost electrochemical energy storage. In order to meet the future needs for energy storage, novel material systems with high energy densities, readily available raw materials, and safety are required. Currently, lithium and lead mainly dominate the battery market, but apart from cobalt and phosphorous, lithium may show substantial supply challenges prospectively, as well. Therefore, the search for new chemistries will become increasingly important in the future, to diversify battery technologies. But which materials seem promising? Using a selection algorithm for the evaluation of suitable materials, the concept of a rechargeable, high-valent all-solid-state aluminum-ion battery appears promising, in which metallic aluminum is used as the negative electrode. On the one hand, this offers the advantage of a volumetric capacity four times higher (theoretically) compared to lithium analog. On the other hand, aluminum is the most abundant metal in the earth's crust. There is a mature industry and recycling infrastructure, making aluminum very cost efficient. This would make the aluminum-ion battery an important contribution to the energy transition process, which has already started globally. So far, it has not been possible to exploit this technological potential, as suitable positive electrodes and electrolyte materials are still lacking. The discovery of inorganic materials with high aluminum-ion mobility—usable as solid electrolytes or intercalation electrodes—is an innovative and required leap forward in the field of rechargeable high-valent ion batteries. In this review article, the constraints for a sustainable and seminal battery chemistry are described, and we present an assessment of the chemical elements in terms of negative electrodes, comprehensively motivate utilizing aluminum, categorize the aluminum battery field, critically review the existing positive electrodes and solid electrolytes, present a promising path for the accelerated development of novel materials and address problems of scientific communication in this field

Rede des Rektors zum 50. Stiftungsfest der Schule

Paul MeutznerProgr.-Nr. 55

Supporting human-machine interaction by robust automatic speech recognition

Im Hinblick auf die zuverlässige Interaktion zwischen Mensch und Maschine bildet die automatische Spracherkennung den Kern dieser Arbeit. Die Arbeit beginnt mit der Untersuchung von akustischen Challenge-Response-Tests, die im Internet als Sicherheitsinstrument verwendet werden, um den Missbrauch von Diensten zu erschweren. Hierauf basierend werden neuartige Tests entwickelt, die ein höheres Maß an Benutzbarkeit und Sicherheit aufweisen als bisher. Des Weiteren werden diverse Methoden der Sprachsignalverbesserung diskutiert, um die Fehlerrate von automatischen Spracherkennungssystemen unter gestörten akustischen Bedingungen zu verringern. Der letzte Teil dieser Arbeit behandelt die Integration von akustischen und visuellen Informationen in multimodalen Spracherkennungssystemen, die auf neuronalen Netzen basieren. Es wird gezeigt, dass die durch ein zusätzliches Verlässlichkeitsmaß gesteuerte Integration der Modalitäten zu deutlich verbesserten Erkennungsraten führt.Aiming towards a reliable interaction between humans and machines, this thesis focuses on automatic speech recognition. The work starts with an investigation of acoustic challenge-response tests that are used as a security measure on the Internet to make the abuse of services harder. Based on this, novel kinds of tests are developed that exhibit a higher degree of usability and security than the current ones. Furthermore, several speech signal enhancement methods are discussed to lower the error rate of automatic speech recognition systems under noisy acoustic conditions. The last part of this work deals with the integration of acoustic and visual information in multi-modal speech recognition systems that are based on deep neural networks. Our results show that an additional reliability measure used for controlling the multi-modal integration leads to clearly improved recognition rates

Untersuchungen hygieinischer Verhältnisse des neuen Gebäudes der Fürsten- und Landesschule St. Afra zu Meissen

eine Abhandlung des Prof. Dr. MeutznerProgr.-Nr. 49