Context-Dependent Acoustic Modeling without Explicit Phone Clustering

Phoneme-based acoustic modeling of large vocabulary automatic speech recognition takes advantage of phoneme context. The large number of context-dependent (CD) phonemes and their highly varying statistics require tying or smoothing to enable robust training. Usually, Classification and Regression Trees are used for phonetic clustering, which is standard in Hidden Markov Model (HMM)-based systems. However, this solution introduces a secondary training objective and does not allow for end-to-end training. In this work, we address a direct phonetic context modeling for the hybrid Deep Neural Network (DNN)/HMM, that does not build on any phone clustering algorithm for the determination of the HMM state inventory. By performing different decompositions of the joint probability of the center phoneme state and its left and right contexts, we obtain a factorized network consisting of different components, trained jointly. Moreover, the representation of the phonetic context for the network relies on phoneme embeddings. The recognition accuracy of our proposed models on the Switchboard task is comparable and outperforms slightly the hybrid model using the standard state-tying decision trees.Comment: Submitted to Interspeech 202

RWTH ASR Systems for LibriSpeech: Hybrid vs Attention -- w/o Data Augmentation

We present state-of-the-art automatic speech recognition (ASR) systems employing a standard hybrid DNN/HMM architecture compared to an attention-based encoder-decoder design for the LibriSpeech task. Detailed descriptions of the system development, including model design, pretraining schemes, training schedules, and optimization approaches are provided for both system architectures. Both hybrid DNN/HMM and attention-based systems employ bi-directional LSTMs for acoustic modeling/encoding. For language modeling, we employ both LSTM and Transformer based architectures. All our systems are built using RWTHs open-source toolkits RASR and RETURNN. To the best knowledge of the authors, the results obtained when training on the full LibriSpeech training set, are the best published currently, both for the hybrid DNN/HMM and the attention-based systems. Our single hybrid system even outperforms previous results obtained from combining eight single systems. Our comparison shows that on the LibriSpeech 960h task, the hybrid DNN/HMM system outperforms the attention-based system by 15% relative on the clean and 40% relative on the other test sets in terms of word error rate. Moreover, experiments on a reduced 100h-subset of the LibriSpeech training corpus even show a more pronounced margin between the hybrid DNN/HMM and attention-based architectures.Comment: Proceedings of INTERSPEECH 201

Antisemitische Gewalt während der Machtergreifungszeit und die Reaktion der deutschen Gesellschaft

In der Reichspogromnacht vom 9. No­vember 1938 wurden 1.400 Synagogen und Beträume, Tausende Wohnun­gen und Geschäfte von Jüdinnen und Juden zerstört und geplündert; mehr mehr als 30.000 Männer in Konzentrationslager verschleppt, un­gefähr hundert wurden ermordet. Dieser vielfach als "Reichskristallnacht" bezeichnete Pogrom, die "Kata­strophe vor der Katastrophe" (Dan Diner), war der Startschuss für die Verdrängung der Juden aus der Wirtschaft und die Arisierung jüdi­schen Eigentums. Er stellte eine Brutalisierung im Umgang mit der jüdischen Bevölkerung dar und war zugleich ein Schritt in Richtung Schoah. Die 75-jährige Wiederkehr der Reichspogromnacht vom 9. auf den 10. No­vember 1938 war für das Landesarchiv Schleswig-Holstein Anlass, dieses Er­eignis im Kontext der jüdischen und der Landes- sowie der nationalsozialis­tischen Gewaltgeschichte erstmals in einer eigenen Ausstellung mit dem Schwerpunkt auf dem Norden Deutschlands zu präsentieren. Die Ausstellung entstand in enger Zusammenarbeit mit der Universität Flensburg und der Landeszentrale für politische Bildung Schleswig-Hol­stein. In Schleswig wurde sie von einer Vortragsreihe begleitet, deren Bei­träge, ergänzt durch weitere Aufsätze, in diesem Band dokumentiert sind. Abbildungen aus der Ausstellung illustrieren die Texte.During the Reichspogromnacht between November 9th and 10th, 1938, in Germany and Austria 1400 synagogues and other Jewish institutions as well as thousands of Jewish homes and shops were destroyed. More than 30.000 men were deported, and at least 100 killed. This pogrom, frequently referred to as „Reichskristallnacht“, marked the beginning of political and economic persecution of Jews in Nazi Germany, and an increasingly brutal treatment of the Jewish minority, thus paving the way for the Holocaust. With regards to the 75th annual recurrence of the Reichspogromnacht, the Landesarchiv Schleswig-Holstein in 2013 presented an exhibition centered around the events of that night in Northern Germany. This exhibition was prepared in close cooperation with the University of Flensburg and the Landeszentrale für politische Bildung Schleswig-Holstein. It was accompanied by a series of lectures that are included in this book as well as some of the illustrations displayed

RASR2: The RWTH ASR Toolkit for Generic Sequence-to-sequence Speech Recognition

Modern public ASR tools usually provide rich support for training various sequence-to-sequence (S2S) models, but rather simple support for decoding open-vocabulary scenarios only. For closed-vocabulary scenarios, public tools supporting lexical-constrained decoding are usually only for classical ASR, or do not support all S2S models. To eliminate this restriction on research possibilities such as modeling unit choice, we present RASR2 in this work, a research-oriented generic S2S decoder implemented in C++. It offers a strong flexibility/compatibility for various S2S models, language models, label units/topologies and neural network architectures. It provides efficient decoding for both open- and closed-vocabulary scenarios based on a generalized search framework with rich support for different search modes and settings. We evaluate RASR2 with a wide range of experiments on both switchboard and Librispeech corpora. Our source code is public online.Comment: accepted at Interspeech 202

Herstellung von Öko-Fleisch- und Öko-Wurstwaren ohne oder mit reduziertem Einsatz von Pökelstoffen

Zweck und Ziel dieses Leitfadens ist es, Verarbeitern, die pökelstofffreie Produkte bzw. Produkte mit reduzierten Mengen von Pökelstoffen herstellen, Hilfestellung in einer angepassten Technologie zu geben. In dem Leitfaden werden die entscheidenden Maßnahmen und entsprechenden Lösungswege aufgezeigt. Der Leitfaden gliedert sich in drei Kapitel: In Kapitel 1 wird die Problematik der Herstellung ohne bzw. mit reduziertem Einsatz von Pökelstoffen erläutert und dargelegt, was aus mikrobiologischer und sensorischer Sicht zu beachten ist und welche Maßnahmen allgemein zu ergreifen sind. In Kapitel 2 werden die Herstellungsweisen einzelner Produkte (Roh-, Brüh, Kochwurst, Roh- und Kochpökelware sowie Konserven) ausführlich und unter Angabe konkreter Kennzahlen behandelt. Kapitel 3 beschäftigt sich mit weitergehenden Ausführungen zu relevanten Themen wie Qualitätssicherung, Berechnung des F-Wertes, Aufschneiden und Verpacken, Lagerung und Durchführung von Haltbarkeitstests sowie die Handhabung von Gewürzen und antioxidativen Zusatzstoffen

GFAP antibodies show protective effect on oxidatively stressed neuroretinal cells via interaction with ERP57

The pathogenesis of glaucoma, a common neurodegenerative disease, involves an immunologic component. Changes in the natural autoantibody profile of glaucoma patients were detected, showing not only up-regulated but also down-regulated immunoreactivities. In recent studies we were able to demonstrate that the antibody changes have a large influence on protein profiles of neuroretinal cells. Furthermore we could demonstrate neuroprotective potential of one of the down-regulated antibodies (gamma-synuclein antibody). Anti-GFAP antibody is another antibody found down-regulated in glaucoma patients. Since GFAP expression is intensified in glaucomatous retina, the aim of this study was to detect the effect of GFAP antibodies on neuroretinal cells. This is realized with a viability-test as well as proteomic analysis of cells incubated with GFAP antibodies. Furthermore, possible interaction partners of the GFAP antibody in neuroretinal cells were identified by western blot, mass spectrometry and indirect immunofluorescence staining. We found that the GFAP antibody is able to protect cells from oxidative stress, which is due to changed protein expressions of the actin cytoskeleton. Furthermore we detected a cross-reaction of the antibody to endoplasmic reticulum resident protein 57 on the cell membrane, which seems to lead to a changed signaling in the cells triggering the protective effects