TY - GEN A1 - Kraljevski, Ivan A1 - Duckhorn, Frank A1 - Sobe, Daniel A1 - Tschöpe, Constanze A1 - Wolff, Matthias ED - Karpov, Alexey ED - Delic, Vlado T1 - Preserving Language Heritage Through Speech Technology: The Case of Upper Sorbian T2 - Speech and Computer, SPECOM 2024, Belgrade, Serbia, 25-28 November 2024 N2 - The modern world is facing a crisis with the rapid disappearance of endangered languages, which poses a serious threat to global cultural diversity. Speech Technologies and Artificial Intelligence present promising opportunities to address this crisis by supporting the documentation, revitalization, and everyday use of these vulnerable languages. However, despite recent and remarkable advancements in speech technology, significant challenges persist, particularly for languages with very limited resources and unique linguistic features. This paper details the development of Upper Sorbian speech technologies, focusing on the creation of a practical Speech-to-Text (STT) system as a versatile tool for language preservation. The study explores the current state of Sorbian languages and underscores collaborative efforts with the Foundation for the Sorbian People. Through a series of pilot and successive projects, each phase has contributed to the steady advancement of speech recognition modules and supporting tools, improving their performance, effectiveness and practical usability. KW - Endangered languages, Speech recognition, Upper Sorbian Y1 - 2024 UR - https://link.springer.com/chapter/10.1007/978-3-031-77961-9_1 SN - 978-3-031-77960-2 SN - 978-3-031-77961-9 U6 - https://doi.org/10.1007/978-3-031-77961-9_1 SP - 3 EP - 22 PB - Springer Nature Switzerland, Cham ER - TY - GEN A1 - Leithoff, Ruben A1 - Dilger, Nikolas A1 - Duckhorn, Frank A1 - Blume, Stefan A1 - Lembcke, Dario A1 - Tschöpe, Constanze A1 - Herrmann, Christoph A1 - Dröder, Klaus T1 - Inline monitoring of battery electrode lamination processes based on acoustic measurements T2 - Batteries N2 - Due to the energy transition and the growth of electromobility, the demand for lithium-ion batteries has increased in recent years. Great demands are being placed on the quality of battery cells and their electrochemical properties. Therefore, the understanding of interactions between products and processes and the implementation of quality management measures are essential factors that requires inline capable process monitoring. In battery cell lamination processes, a typical problem source of quality issues can be seen in missing or misaligned components (anodes, cathodes and separators). An automatic detection of missing or misaligned components, however, has not been established thus far. In this study, acoustic measurements to detect components in battery cell lamination were applied. Although the use of acoustic measurement methods for process monitoring has already proven its usefulness in various fields of application, it has not yet been applied to battery cell production. While laminating battery electrodes and separators, acoustic emissions were recorded. Signal analysis and machine learning techniques were used to acoustically distinguish the individual components that have been processed. This way, the detection of components with a balanced accuracy of up to 83% was possible, proving the feasibility of the concept as an inline capable monitoring system. Y1 - 2021 U6 - https://doi.org/10.3390/batteries7010019 SN - 2313-0105 VL - 7 IS - 1 SP - 1 EP - 21 PB - MDPI AG CY - Basel ER - TY - GEN A1 - Lieske, Uwe A1 - Duckhorn, Frank A1 - Tschöpe, Constanze A1 - Harig, Paul A1 - Pallmer, Matthias A1 - Röder, Olaf A1 - Röder, Elisabeth T1 - Verfahren zur akustischen Detektion von Schadinsekten bei der Getreide- und Saatgutlagerung T2 - DGZfP-Jahrestagung Zerstörungsfreie Materialprüfung 2017 : Kurzfassungen der Vorträge und Posterbeiträge : 22.-24. Mai 2017, Koblenz N2 - Getreide bildet eine der wichtigsten Grundlagen für die menschliche und tierische Ernährung. Wie jedes andere pflanzliche Produkt, so ist jedoch Getreide auch Nahrungsquelle für zahlreiche Insekten, die während des Pflanzenwachstums und der Lagerung das Korn befallen können. Jährlich werden etwa 10 % der weltweiten Getreideernte durch Schadinsekten vernichtet. In der Praxis wird der Befall mit Schadinsekten im Rahmen von Stichproben durch visuelle Inspektion, Sieben oder Aufschwemmen der Getreidekörner dokumentiert. Es werden auch einfache Handgeräte mit Mikrofon und Verstärker eingesetzt, um Schädlingsbefall durch Fressgeräusche manuell zu erkennen. Eine frühzeitige Diagnose des Auftretens von Vorratsschädlingen ist für die Einleitung von Gegenmaßnahmen und die Begrenzung des Schadens von großer Bedeutung. Das hier vorgestellte Verfahren bietet die Möglichkeit, die auftretenden Geräusche automatisiert zu analysieren, und ermöglicht so eine schnelle und zuverlässige Erkennung von Schadinsekten. Im Rahmen der Untersuchungen wurden die auftretenden Geräusche von Schadinsekten in den verschiedenen Entwicklungsstadien analysiert und eine geeignete Signalerfassungshardware für den Feldeinsatz entwickelt. Mit den implementierten Signalverarbeitungsalgorithmen der akustischen Mustererkennung erfolgt die automatisierte Auswertung und Klassifizierung der Schädlingsgeräusche. Das Verfahren, die Hardware und die Messergebnisse werden vorgestellt. Y1 - 2017 UR - https://www.ndt.net/article/dgzfp2017/papers/p52.pdf PB - Deutsche Gesellschaft für Zerstörungsfreie Prüfung e.V. CY - Berlin ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Joneit, Dieter A1 - Duckhorn, Frank A1 - Hoffmann, Rüdiger A1 - Strecha, Guntram A1 - Wolff, Matthias T1 - Sprachsteuerung für Mess- und Prüfgeräte T2 - DGZfP-Jahrestagung 2011 Zerstörungsfreie Materialprüfung, 30. Mai - 1. Juni 2011, Bremen, Berichtsband Y1 - 2011 SN - 978-3-940283-33-7 PB - DGZfP CY - Berlin ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Wolff, Matthias A1 - Duckhorn, Frank T1 - Zustandsüberwachung von Magnetventilen anhand der Schaltgeräusche T2 - ZfP in Forschung, Entwicklung und Anwendung, Potsdam, 26. - 28. Mai 2014, DGZfP-Jahrestagung 2014 Y1 - 2014 SN - 978-3-940283-61-0 PB - DGZfP CY - Berlin ER - TY - GEN A1 - Kraljevski, Ivan A1 - Duckhorn, Frank A1 - Ju, Yong Chul A1 - Tschöpe, Constanze A1 - Richter, Christian A1 - Wolff, Matthias T1 - Acoustic Resonance Recognition of Coins T2 - 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 25-28 May 2020, Dubrovnik, Croatia N2 - In this study, we compare different machine learning approaches applied to acoustic resonance recognition of coins. Euro-cents and Euro-coins were classified by the sound emerging when throwing the coins onto a hard surface.The used dataset is a representative example of a small data which was collected in carefully prepared experiments.Due to the small number of coin specimens and the count of the collected observations, it was interesting to see whether deep learning methods can achieve similarly or maybe even better classification performances compared with more traditional methods.The results of the multi-class prediction of coin denominations are presented and compared in terms of balanced accuracy and Matthews Correlation Coefficient metrics. The feature analysis methods combined with the employed classifiers achieved acceptable results, despite the relatively small dataset. Y1 - 2020 SN - 978-1-7281-4460-3 SN - 978-1-7281-4461-0 U6 - https://doi.org/10.1109/I2MTC43012.2020.9129256 PB - IEEE Xplore ER - TY - GEN A1 - Kraljevski, Ivan A1 - Duckhorn, Frank A1 - Ju, Yong Chul A1 - Tschöpe, Constanze A1 - Wolff, Matthias ED - Maglogiannis, Ilias ED - Iliadis, Lazaros S. ED - Pimenidis, Elias T1 - Acoustic Resonance Testing of Glass IV Bottles T2 - Artificial Intelligence Applications and Innovations : 16th IFIP WG 12.5 International Conference, AIAI 2020, Neos Marmaras, Greece, June 5–7, 2020, Proceedings, Part II N2 - In this paper, acoustic resonance testing on glass intravenous (IV) bottles is presented. Different machine learning methods were applied to distinguish acoustic observations of bottles with defects from the intact ones. Due to the very limited amount of available specimens, the question arises whether the deep learning methods can achieve similar or even better detection performance compared with traditional methods. Y1 - 2020 SN - 978-3-030-49186-4 SN - 978-3-030-49185-7 U6 - https://doi.org/10.1007/978-3-030-49186-4_17 SN - 1868-4238 SN - 1868-422X VL - Cham SP - 195 EP - 206 PB - Springer International Publishing ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Duckhorn, Frank A1 - Huber, Markus A1 - Meyer, Werner A1 - Wolff, Matthias ED - Karpov, Alexey ED - Jokisch, Oliver ED - Potapova, Rodmonga T1 - A Cognitive User Interface for a Multi-Modal Human-Machine Interaction T2 - Speech and computer : 20th International Conference, SPECOM 2018, Leipzig, Germany, September 18-22, 2018, proceedings Y1 - 2018 UR - https://link.springer.com/chapter/10.1007/978-3-319-99579-3_72 SN - 978-3-319-99578-6 U6 - https://doi.org/10.1007/978-3-319-99579-3 SP - 707 EP - 717 PB - Springer International Publishing CY - Cham ER - TY - GEN A1 - Duckhorn, Frank A1 - Huber, Markus A1 - Meyer, Werner A1 - Jokisch, Oliver A1 - Tschöpe, Constanze A1 - Wolff, Matthias ED - Lacerda, Francisco T1 - Towards an Autarkic Embedded Cognitive User Interface T2 - Proceedings Interspeech 2017, 20-24 August 2017, Stockholm N2 - ucuikt2015 Y1 - 2017 UR - http://www.isca-speech.org/archive/Interspeech_2017/ U6 - https://doi.org/10.21437/Interspeech.2017 SP - 3435 EP - 3436 PB - ISCA ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Duckhorn, Frank A1 - Richter, Christian A1 - Blüthgen, Peter A1 - Wolff, Matthias T1 - Intelligent Signal Processing on a Miniaturized Hardware Module T2 - IEEE SENSORS Proceedings, Glasgow, Scotland, UK, Oct. 29 - Nov. 1, 2017 Y1 - 2017 UR - http://ieeexplore.ieee.org/document/8234023/ SN - 978-1-5090-1012-7 U6 - https://doi.org/10.1109/ICSENS.2017.8234023 N1 - IEEE Catalog Numer: CFP17SEN-ART PB - IEEE CY - Piscataway, NJ ER -