TY - GEN A1 - Römer, Ronald A1 - beim Graben, Peter A1 - Huber, Markus A1 - Klimczak, Peter A1 - Wirsching, Günther A1 - Wolff, Matthias ED - Wendemuth, Andreas ED - Böck, Ronald ED - Siegert, Ingo T1 - Die Welt ist nicht genug! Man muss auch über sie sprechen können T2 - Elektronische Sprachsignalverarbeitung 2020 : Tagungsband der 31. Konferenz Magdeburg, 4. - 6. März 2020 Y1 - 2020 SN - 978-3-95908-193-1 SN - 0940-6832 SP - 173 EP - 184 PB - TUDpress CY - Dresden ER - TY - PAT A1 - Wolff, Matthias A1 - Römer, Ronald A1 - Tschöpe, Constanze A1 - Hentschel, Dieter T1 - Verfahren und Vorrichtung zur Verhaltenssteuerung von Systemen Y1 - 2020 ER - TY - GEN A1 - Römer, Ronald A1 - beim Graben, Peter A1 - Huber-Liebl, Markus A1 - Wolff, Matthias T1 - Unifying Physical Interaction, Linguistic Communication, and Language Acquisition of Cognitive Agents by Minimalist Grammars T2 - Frontiers in Computer Science N2 - Cognitive agents that act independently and solve problems in their environment on behalf of a user are referred to as autonomous. In order to increase the degree of autonomy, advanced cognitive architectures also contain higher-level psychological modules with which needs and motives of the agent are also taken into account and with which the behavior of the agent can be controlled. Regardless of the level of autonomy, successful behavior is based on interacting with the environment and being able to communicate with other agents or users. The agent can use these skills to learn a truthful knowledge model of the environment and thus predict the consequences of its own actions. For this purpose, the symbolic information received during the interaction and communication must be converted into representational data structures so that they can be stored in the knowledge model, processed logically and retrieved from there. Here, we firstly outline a grammar-based transformation mechanism that unifies the description of physical interaction and linguistic communication and on which the language acquisition is based. Specifically, we use minimalist grammar (MG) for this aim, which is a recent computational implementation of generative linguistics. In order to develop proper cognitive information and communication technologies, we are using utterance meaning transducers (UMT) that are based on semantic parsers and a mental lexicon, comprising syntactic and semantic features of the language under consideration. This lexicon must be acquired by a cognitive agent during interaction with its users. To this aim we outline a reinforcement learning algorithm for the acquisition of syntax and semantics of English utterances. English declarative sentences are presented to the agent by a teacher in form of utterance meaning pairs (UMP) where the meanings are encoded as formulas of predicate logic. Since MG codifies universal linguistic competence through inference rules, thereby separating innate linguistic knowledge from the contingently acquired lexicon, our approach unifies generative grammar and reinforcement learning, hence potentially resolving the still pending Chomsky-Skinner controversy. btuktuminglear, btuktsptech, btuktcogsys Y1 - 2022 UR - https://www.frontiersin.org/article/10.3389/fcomp.2022.733596 U6 - https://doi.org/10.3389/fcomp.2022.733596 SN - 2624-9898 IS - 4 ER - TY - GEN A1 - Meyer, Werner A1 - Borislavov, Borislav A1 - Eckert, Friedrich A1 - Richter, Christian A1 - Römer, Ronald A1 - Beim Graben, Peter A1 - Huber, Markus A1 - Wolff, Matthias ED - Hillmann, Stefan ED - Weiss, Benjamin ED - Michael, Thilo ED - Möller, Sebastian T1 - Formalisierung und Implementierung einer adaptiven kognitiven Architektur unter Verwendung von Strukturdiagrammen T2 - Elektronische Sprachsignalverarbeitung 2021 : Tagungsband der 32. Konferenz Berlin, 3.-5. März 2021 N2 - Das Fachgebiet der Kognitiven Technischen Systeme zeichnet sich durch einen hohen Grad an Interdisziplinarität (z. B. Kenntnisse auf den Gebieten Biologie, Psychologie, Informatik und den Ingenieurwissenschaften) aus. Nach wie vor besteht Bedarf an einer methodischen Darstellung des Fachgebietes, bei der die theoretische Durchdringung von Zusammenhängen zwischen den verschiedenen Wissensgebieten zusätzlich durch Anschaulichkeit unterstützt wird. Die vorliegende Arbeit stellt einen Fortschrittsbericht zur Realisierung eines Forschungs- und Experimentiersystems dar, mit dem wir dieses Anliegen unterstützen und über das wir erstmals konzeptionell in [1] berichtet haben. In diesem Beitrag folgen wir einem integrativen Ansatz zur Entwicklung einer kognitiven Architektur, mit der unter Verwendung repräsentationaler Datenstrukturen adaptives Verhalten auf verschiedenen Zeitskalen sowie zwei wichtige Verhaltensprogramme für das Problemlösen (Objektfindung, Exploration) auf der gemeinsamen Grundlage von Markov-Entscheidungsprozessen umgesetzt werden. Mit einem Kurzbericht zum Entwicklungsstand der physikalischen Experimentierumgebung und einer Zusammenfassung der bislang erreichten Ergebnisse beschließen wir den diesjährigen Beitrag. Y1 - 2021 UR - https://www.essv.de/?year=2021 SN - 978-3-959082-27-3 SN - 0940-6832 SP - 67 EP - 76 PB - TUDpress CY - Dresden ER - TY - GEN A1 - Beim Graben, Peter A1 - Huber, Markus A1 - Meyer, Werner A1 - Römer, Ronald A1 - Wolff, Matthias T1 - Vector Symbolic Architectures for Context-Free Grammars T2 - Cognitive Computation N2 - Vector symbolic architectures (VSA) are a viable approach for the hyperdimensional representation of symbolic data, such as documents, syntactic structures, or semantic frames. We present a rigorous mathematical framework for the representation of phrase structure trees and parse trees of context-free grammars (CFG) in Fock space, i.e. infinite-dimensional Hilbert space as being used in quantum field theory. We define a novel normal form for CFG by means of term algebras. Using a recently developed software toolbox, called FockBox, we construct Fock space representations for the trees built up by a CFG left-corner (LC) parser. We prove a universal representation theorem for CFG term algebras in Fock space and illustrate our findings through a low-dimensional principal component projection of the LC parser state. Our approach could leverage the development of VSA for explainable artificial intelligence (XAI) by means of hyperdimensional deep neural computation. Y1 - 2021 U6 - https://doi.org/10.1007/s12559-021-09974-y SN - 1866-9964 VL - 14 IS - 2 SP - 733 EP - 748 ER - TY - GEN A1 - Huber-Liebl, Markus A1 - Römer, Ronald A1 - Wirsching, Günther A1 - Schmitt, Ingo A1 - beim Graben, Peter A1 - Wolff, Matthias T1 - Quantum-inspired Cognitive Agents T2 - Frontiers in Applied Mathematics and Statistics N2 - The concept of intelligent agents is—roughly speaking—based on an architecture and a set of behavioral programs that primarily serve to solve problems autonomously. Increasing the degree of autonomy and improving cognitive performance, which can be assessed using cognitive and behavioral tests, are two important research trends. The degree of autonomy can be increased using higher-level psychological modules with which needs and motives are taken into account. In our approach we integrate these modules in architecture for an embodied, enactive multi-agent system, such that distributed problem solutions can be achieved. Furthermore, after uncovering some weaknesses in the cognitive performance of traditionally designed agents, we focus on two major aspects. On the one hand, the knowledge processing of cognitive agents is based on logical formalisms, which have deficiencies in the representation and processing of incomplete or uncertain knowledge. On the other hand, in order to fully understand the performance of cognitive agents, explanations at the symbolic and subsymbolic levels are required. Both aspects can be addressed by quantum-inspired cognitive agents. To investigate this approach, we consider two tasks in the sphere of Shannon's famous mouse-maze problem: namely classifying target objects and ontology inference. First, the classification of an unknown target object in the mouse-maze, such as cheese, water, and bacon, is based on sensory data that measure characteristics such as odor, color, shape, or nature. For an intelligent agent, we need a classifier with good prediction accuracy and explanatory power on a symbolic level. Boolean logic classifiers do work on a symbolic level but are not adequate for dealing with continuous data. Therefore, we demonstrate and evaluate a quantum-logic-inspired classifier in comparison to Boolean-logic-based classifiers. Second, ontology inference is iteratively achieved by a quantum-inspired agent through maze exploration. This requires the agent to be able to manipulate its own state by performing actions and by collecting sensory data during perception. We suggest an algebraic approach where both kinds of behaviors are uniquely described by quantum operators. The agent's state space is then iteratively constructed by carrying out unitary action operators, while Hermitian perception operators act as observables on quantum eigenstates. As a result, an ontology emerges as the simultaneous solution of the respective eigenvalue equations. Tags: btuktqiai; btuktcogsys; btukttheseus; btuktqtheseus Y1 - 2022 UR - https://www.frontiersin.org/articles/10.3389/fams.2022.909873 U6 - https://doi.org/10.3389/fams.2022.909873 SN - 2297-4687 IS - 8 SP - 1 EP - 31 ER - TY - GEN A1 - Maier, Isidor Konrad A1 - Wolff, Matthias T1 - A Decomposition Algorithm for Numerals based on Arithmetics N2 - Poster presentation for an idea to decompose numerals Y1 - 2022 U6 - https://doi.org/10.5281/zenodo.7501698 ER - TY - GEN A1 - Tschöpe, Constanze A1 - Kraljevski, Ivan A1 - Duckhorn, Frank A1 - Wolff, Matthias T1 - Sprachtechnologie und akustische Mustererkennung in der medizinischen Anwendung T2 - 16. Landeskonferenz „Digitalisierung im Gesundheitswesen“ 2021 Y1 - 2021 UR - https://www.digital-agentur.de/veranstaltungen/telemed UR - https://www.digital-agentur.de/fileadmin/06_Bilddatenbank/Gesundheit/Telemed/Praesentationen/Tscho__pe_Impuls_Telemed21.pdf ER - TY - GEN A1 - Römer, Ronald A1 - beim Graben, Peter A1 - Huber-Liebl, Markus A1 - Wolff, Matthias T1 - (Pre-)linguistic Problem Solving based on Dynamic Semantics T2 - 14th IEEE International Conference on Cognitive Infocommunications – CogInfoCom 2023, September 22-23, Budapest, Hungary Y1 - 2023 SN - 979-8-3503-2565-2 SN - 979-8-3503-2566-9 U6 - https://doi.org/10.1109/CogInfoCom59411.2023.10397487 SN - 2473-5671 SN - 2380-7350 SP - 147 EP - 152 ER - TY - GEN A1 - Maier, Isidor Konrad A1 - Kuhn, Johannes A1 - Beisegel, Jesse A1 - Huber-Liebl, Markus A1 - Wolff, Matthias T1 - Minimalist Grammar: Construction without Overgeneration T2 - arXiv N2 - In this paper we give instructions on how to write a minimalist grammar (MG). In order to present the instructions as an algorithm, we use a variant of context free grammars (CFG) as an input format. We can exclude overgeneration, if the CFG has no recursion, i.e. no non-terminal can (indirectly) derive to a right-hand side containing itself. The constructed MGs utilize licensors/-ees as a special way of exception handling. A CFG format for a derivation A_eats_B↦∗peter_eats_apples, where A and B generate noun phrases, normally leads to overgeneration, e.\,g., i_eats_apples. In order to avoid overgeneration, a CFG would need many non-terminal symbols and rules, that mainly produce the same word, just to handle exceptions. In our MGs however, we can summarize CFG rules that produce the same word in one item and handle exceptions by a proper distribution of licensees/-ors. The difficulty with this technique is that in most generations the majority of licensees/-ors is not needed, but still has to be triggered somehow. We solve this problem with ϵ-items called \emph{adapters}. Y1 - 2023 UR - https://arxiv.org/abs/2311.01820 U6 - https://doi.org/10.48550/arXiv.2311.01820 ER - TY - GEN A1 - Kuhn, Johannes A1 - Wolff, Matthias A1 - Borislavov, Borislav T1 - Epsilon-Verarbeitung bei Minimalistischen Grammatiken für Zahlen T2 - Elektronische Sprachsignalverarbeitung, Tagungsband der 35. Konferenz, 06.-08.03.2024, Regensburg N2 - Um bei Minimalistischen Grammatiken (MG) Übergenerierung zu vermeiden, kann man Einträge mit leeren Exponenten (ε-Einträge) verwenden. Ein Eintrag besteht aus einem Exponenten, der die Äußerung oder Schrift eines Wortes repräsentiert, einer Merkmalsliste, welche die Syntax kodiert und einem λ-Ausdruck, der die Semantik repräsentiert. Leere Einträge führen allerdings zu einer schlechteren Verwendbarkeit der Grammatik für das Parsen. Die vorliegende Arbeit wird ein Umformungsalgorithmus für MGs vorstellen, sodass die Anzahl der ε-Einträge verringert werden kann, um sie wieder für Parser verwendbar zu machen. Hierzu werden die ε-Einträge mit den anderen Einträgen vorverarbeitet und dadurch neue Einträge geschaffen. Die nun überflüssigen ε-Einträge können dann problemlos entfernt werden. Der Algorithmus wurde anhand von über 260 Zahlwortgrammatiken getestet. Y1 - 2024 UR - https://www.essv.de/pdf/2024_78_85.pdf?id=1208 SN - 978-3-95908-325-6 SN - 0940-6832 SP - 78 EP - 85 PB - TUDpress CY - Dresden ER - TY - GEN A1 - Kuhn, Johannes A1 - Wolff, Matthias A1 - Maier, Isidor Konrad ED - Grawunder, Sven T1 - Wortgenerator für Minimalistische Grammatiken T2 - Elektronische Sprachsignalverarbeitung, Tagungsband der 36. Konferenz, 05.-07.03.2025, Halle/Saale N2 - Um eine bidirektionale Verarbeitung von Sprache zu realisieren, ist es von Vorteil den gleichen Sprachformalismus für das Parsen und die Generierung zu verwenden. Für Minimalistische Grammatiken gibt es eine ausgeprägte Literatur zu Parsern, aber noch keine Veröffentlichung zu Generatoren. Diese Arbeit stellt einen ersten Generator vor, der mittels Minimalistischer Grammatiken und λ-Ausdrücken, Sätze erzeugt. Der hier vorgestellte Generator kann entgegen manchen anderen Generatoren, von anderen Grammatikformalismen, mit ε-Regeln arbeiten. Y1 - 2025 UR - https://www.essv.de/pdf/2025_27_34.pdf SN - 978-3-95908-803-9 SN - 0940-6832 SP - 27 EP - 34 PB - TUDpress CY - Dresden ER - TY - GEN A1 - Huber-Liebl, Markus A1 - Rosenow, Tillmann A1 - Römer, Ronald A1 - Wirsching, Günther A1 - Wolff, Matthias ED - Grawunder, Sven T1 - It all starts with a little difference : tensors as data and code. T2 - Elektronische Sprachsignalverarbeitung 2025 : Tagungsband der 36. Konferenz Halle/Saale, 5.–7. März 2025 N2 - We further promote the idea of quantum inspiration and propose to equip cognitive systems not only with tensors for data representation but also for operation representation. We argue that these are two sides of the same coin. For experimental symbolic algorithms we introduce a suitable testbed and give its proper specification. We formalize our method of behavioural control with tensor algebra and discuss its implementation for our physical testbed realization. Y1 - 2025 UR - https://www.essv.de/pdf/2025_170_179.pdf?id=1250 SN - 978-3-95908-803-9 SN - 0940-6832 SP - 170 EP - 179 PB - TUDpress CY - Dresden ER - TY - GEN A1 - Maier, Isidor Konrad A1 - Rosenow, Tillmann A1 - Tuuri, Okko A1 - Wolff, Matthias ED - Grawunder, Sven T1 - Frequency-magnitude relation of numeral words based on search-engine results T2 - Elektronische Sprachsignalverarbeitung, Tagungsband der 36. Konferenz, 05.-07.03.2025, Halle/Saale N2 - We googled various numeral words from 28 languages. Different approaches for the description of the data were investigated. In all of the 28 languages, the found frequency-magnitude dependence fits better to a power law than to an exponential law. The result can be used to distinguish grammatically correct from incorrect numerals based on the prediction of search results. Y1 - 2025 UR - http://www.essv.de SN - 978-3-95908-803-9 SN - 0940-6832 SP - 51 EP - 60 PB - TUDpress CY - Dresden ER - TY - CHAP A1 - Wolff, Matthias A1 - Schubert, R. A1 - Hoffmann, Rüdiger A1 - Tschöpe, Constanze A1 - Schulze, E. A1 - Neunübel, H. T1 - Experiments in Acoustic Structural Health Monitoring of Airplane Parts T2 - IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2008), 30.3.-4.4.2008, Las Vegas, USA Y1 - 2008 SN - 978-1-4244-1483-3 U6 - https://doi.org/10.1109/ICASSP.2008.4518040 SP - 2037 EP - 2040 PB - IEEE ER - TY - CHAP A1 - Strecha, Guntram A1 - Wolff, Matthias A1 - Duckhorn, Frank A1 - Wittenberg, Sören A1 - Tschöpe, Constanze T1 - The HMM synthesis algorithm of an embedded unified speech recognizer and synthesizer T2 - Proceedings of the Annual Conference of the International Speech Communication Association 2009, Interspeech 2009, 6 - 10 September, 2009, Brighton, UK Y1 - 2009 SP - 1763 EP - 1766 PB - ISCA CY - Brighton ER - TY - GEN A1 - Pusch, T. A1 - Cherif, Chokri A1 - Farooq, Aamir A1 - Wittenberg, Sören A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger A1 - Tschöpe, Constanze T1 - Fehlerfrüherkennung an Textilmaschinen mit Hilfe der Körperschallanalyse T2 - Melliand Textilberichte Y1 - 2009 SN - 0341-0781 VL - 90 IS - 3 SP - 113 EP - 115 ER - TY - CHAP A1 - Wolff, Matthias A1 - Tschöpe, Constanze T1 - Pattern recognition for sensor signals T2 - Proceedings of the IEEE Sensors Conference 2009, Christchurch, New Zealand, 25 - 28 October 2009 Y1 - 2009 SN - 978-1-424-44548-6 SN - 978-1-4244-5335-1 U6 - https://doi.org/10.1109/ICSENS.2009.5398338 SP - 665 EP - 668 PB - IEEE CY - Piscataway, NJ ER - TY - THES A1 - Wolff, Matthias T1 - Akustische Mustererkennung Y1 - 2011 SN - 978-3-942710-14-5 PB - TUDpress CY - Dresden ER - TY - GEN A1 - Li, Huajian A1 - Kraljevski, Ivan A1 - Meyer, Paul A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - YOLO-ICP : deep learning integrated pose estimation for bin-picking of multiple objects T2 - 2024 IEEE SENSORS, Proceedings, Kobe, Japan, 2024 N2 - In this paper, we present a novel deep learning-integrated pipeline called YOLO-ICP that aims to estimate the six degree of freedom (6-DoF) pose of objects using RGB-D sensors and does not require pose labels to train deep learning networks. YOLO-ICP integrates a real-time object detection algorithm with a point cloud registration method to estimate the pose of multiple objects. We evaluated our approach by quantitatively comparing it with baseline models on the OccludedLINEMOD dataset. Experimental results illustrate that our approach outperforms baseline models in challenging scenarios with textureless and occluded objects. In particular, our pipeline shows superior performance when dealing with small and symmetric objects in terms of the ADD(-S) metric. KW - Pose estimation KW - Deep learning KW - CAD KW - Point cloud KW - Bin-picking KW - RGB-D camera Y1 - 2024 SN - 979-8-3503-6351-7 U6 - https://doi.org/10.1109/SENSORS60989.2024.10784539 SP - 1 EP - 4 PB - Institute of Electrical and Electronics Engineers (IEEE) CY - Piscataway, New Jersey ER - TY - GEN A1 - Kraljevski, Ivan A1 - Duckhorn, Frank A1 - Sobe, Daniel A1 - Tschöpe, Constanze A1 - Wolff, Matthias ED - Grawunder, Sven T1 - Speech-to-text in upper sorbian : current state T2 - Elektronische Sprachsignalverarbeitung 2025 : Tagungsband der 36. Konferenz Halle/Saale, 5.–7. März 2025 N2 - This study presents recent advancements in Upper Sorbian Speech-to-Text (STT) technology. We provide an overview of the Sorbian languages, the available speech and language resources, and the development of an STT system based on a traditional approach, which includes acoustic, pronunciation, and language modeling. Due to the scarcity of resources for Sorbian languages, our approach leverages sub-word and word-class modeling techniques. The word-class modeling is based on Finite-State Transducer definitions, which are applicable to both offline text parsing and integration into the decoding graph of the STT system. Word-class parsing is performed on the speech corpus and utilized for language modeling with complete words, sub-word units, or both. Additionally, the same definitions can be applied to Named Entity Recognition during the post-processing of recognized transcriptions. This approach significantly reduces out-of-vocabulary words and enables greater customization of the recognizer for domain-specific applications. The system was implemented for the real-time transcription of church sermon broadcasts in Upper Sorbian. The domain-specific system achieved performance comparable to fine-tuned OpenAI Whisper models developed also by other initiatives while also providing a resource-efficient solution with semantically tagged recognition results. Y1 - 2025 UR - https://www.essv.de/pdf/2025_109_116.pdf SN - 978-3-95908-803-9 SN - 0940-6832 SP - 109 EP - 116 PB - TUDpress CY - Dresden ER - 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 - PAT A1 - Saeltzer, Gerhard A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - Vorrichtung und Verfahren zur Bestimmung eines medizinischen Gesundheitsparameters eines Probanden mittels Stimmanalyse N2 - Eine Vorrichtung zur Bestimmung eines Gesundheitsparameters eines Probanden mittels Stimmauswertung umfasst eine Verarbeitungseinrichtung, die ausgebildet ist, um eine digitalisierte Sprechprobe des Probanden basierend auf individuellen Modellparametern auszuwerten, um eine Messinformation zu erhalten, die innerhalb eines Toleranzbereichs auf einem Momentanwert des Gesundheitsparameters des Probanden basiert, wobei die individuellen Modellparameter einen funktionalen Zusammenhang zwischen der Sprechprobe oder von der Sprechprobe abgeleiteten Sprechmerkmalen und einem zugeordneten, momentanen Gesundheitsparameter angeben. Y1 - 2024 UR - https://depatisnet.dpma.de/DepatisNet/depatisnet?window=1&space=menu&content=treffer&action=bibdat&docid=DE102015218948A1 ER - TY - PAT A1 - Wolff, Matthias A1 - Römer, Ronald A1 - Tschöpe, Constanze A1 - Hentschel, Dieter T1 - Method and Device for Controlling the Behavior of Systems T1 - Verfahren und Vorrichtung zur Verhaltenssteuerung von Systemen T1 - Procede et dispositif de commande du comportement de systemes Y1 - 2022 UR - https://register.epo.org/application?number=EP14749730&lng=en&tab=main ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - Automatic decision making in SHM using hidden Markov models T2 - 18th International Conference on Database and Expert Systems Applications (DEXA 2007), Regensburg, September 3-7, 2007 Y1 - 2007 U6 - https://doi.org/10.1109/DEXA.2007.138 SP - 307 EP - 311 PB - IEEE ER - TY - GEN A1 - Tschöpe, Constanze A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger T1 - Akustische Mustererkennung für die ZfP T2 - MP Materials Testing Y1 - 2009 SN - 0025-5300 VL - 51 IS - 10 SP - 701 EP - 704 ER - TY - CHAP A1 - Kordon, Ulrich A1 - Wolff, Matthias A1 - Tschöpe, Constanze ED - Gerlach, Gerald T1 - Mustererkennung für Sensorsignale Y1 - 2009 SN - 978-3-941298-55-2 SP - 69 EP - 78 PB - TUDpress CY - Dresden ER - TY - GEN A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - Statistical Classifiers for Structural Health Monitoring T2 - IEEE sensors journal Y1 - 2009 U6 - https://doi.org/10.1109/JSEN.2009.2019330 SN - 1530-437X VL - 9 IS - 11 SP - 1567 EP - 1576 ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - Instrumentelle Bestimmung der Weichheit von Tissueprodukten T2 - Forum Akustische Qualitätssicherung 2010 der DGAQS, 03. und 04. November 2010 in Karlsruhe Y1 - 2010 SP - 3-1 EP - 3-3 PB - DGaQs CY - Karlsruhe ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger ED - Becker-Schweitzer, Jörg T1 - Akustische Mustererkennung T2 - DAGA 2011, 37. Jahrestagung für Akustik, Düsseldorf, 21. - 24. 3. 2011, Tagungsband "Fortschritte der Akustik" Y1 - 2011 SN - 978-3-939296-02-7 SP - 345 EP - 346 PB - Dt. Gesellschaft für Akustik CY - Berlin ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Wolff, Matthias ED - Wolff, Matthias T1 - Zur Formulierung von Hidden-Markov-Modellen als endliche Transduktoren T2 - Elektronische Sprachsignalverarbeitung 2012, Tagungsband der 23. Konferenz, Cottbus, 29. - 31. August 2012 Y1 - 2012 SN - 978-3-942710-81-7 SP - 120 EP - 128 PB - TUDpress CY - Dresden 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 - Wolff, Matthias A1 - Tschöpe, Constanze A1 - Römer, Ronald A1 - Wirsching, Günther ED - Wagner, Petra T1 - Subsymbol-Symbol-Transduktoren T2 - Elektronische Sprachsignalverarbeitung 2013, Tagungsband, Bielefeld, 2013 Y1 - 2013 SN - 978-3-94431-03-4 SP - 197 EP - 204 PB - TUDpress CY - Dresden ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger ED - Wagner, Petra T1 - Anwendungen der akustischen Mustererkennung T2 - Elektronische Sprachsignalverarbeitung 2013, Tagungsband, Bielefeld, 2013 Y1 - 2013 SN - 978-3-94431-03-4 SP - 205 EP - 210 PB - TUDpress CY - Dresden 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 - CHAP A1 - Wolff, Matthias A1 - Tschöpe, Constanze A1 - Römer, Ronald ED - Mehnert, Dieter ED - Kordon, Ulrich ED - Wolff, Matthias T1 - Quo vadis, UASR? T2 - Systemtheorie Signalverarbeitung Sprachtechnologie Y1 - 2013 SN - 978-3-944331-19-5 SP - 276 EP - 285 PB - TUDpress CY - Dresden ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - Processing and evaluation of gear data using statistical classifiers T2 - Proceedings of the 6th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2012), Vienna, Sep. 2012 Y1 - 2012 SN - 978-395-02481-9-7 CY - Vienna 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 - TY - CHAP A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - Mustererkennung in der technischen Diagnose T2 - Tagungsband der 12. Tagung Technische Diagnostik 2016, 20.-21.10.2016, Hochschule Merseburg Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:3:2-68977 UR - https://www.hs-merseburg.de/fileadmin/redaktion/Weiterbildung/Tagungsband_12._Tagung_Technische_Diagnostik.pdf SN - 978-3-942703-64-2 N1 - Untersützt vom VDI Bezirksverein Halle SP - 124 EP - 125 PB - Hochschule Merseburg CY - Merseburg ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Duckhorn, Frank A1 - Richter, Christian A1 - Blüthgen, Peter A1 - Wolff, Matthias T1 - An embedded system for acoustic pattern recognition T2 - IEEE SENSORS Proceedings, Glasgow, Scotland, UK, Oct. 29 - Nov. 1, 2017 Y1 - 2017 SN - 978-1-5090-1012-7 U6 - https://doi.org/10.1109/ICSENS.2017.8234380 N1 - IEEE Catalog Numer: CFP17SEN-ART PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Wolff, Matthias A1 - Saeltzer, G. T1 - Estimating blood sugar from voice samples : a preliminary study T2 - 2015 International Conference on Computational Science and Computational Intelligence (CSCI 2015), Las Vegas, December 7-9, 2015 Y1 - 2015 U6 - https://doi.org/10.1109/CSCI.2015.184 SP - 804 EP - 805 PB - IEEE ER - TY - GEN A1 - Tschöpe, Constanze A1 - Mühle, Maximilian A1 - Ju, Yong Chul A1 - Kraljevski, Ivan A1 - Wolff, Matthias T1 - Künstliche Intelligenz in der ZfP - Welchen Beitrag kann KI in der ZfP leisten? T2 - DGZfP-Jahrestagung 2021, 10.-11. Mai N2 - Künstliche Intelligenz zieht derzeit in alle Bereiche der Gesellschaft und des Lebens ein. Aber welchen Stellenwert hat sie momentan auf dem Gebiet der zerstörungsfreien Prüfung? Was kann KI leisten? Welche Herausforderungen müssen erfolgreich bewältigt werden? Gibt es das eine KI-Verfahren, welches prinzipiell für ZfP geeignet ist? Bei der Bauteil- und Materialprüfung während und unmittelbar nach der Herstellung, der Überwachung von Verschleißteilen in Maschinen und Anlagen oder der Schadensdetektion an Bauteilen und Komponenten liefern ZfP-Verfahren Daten, die bewertet werden müssen. Obwohl inzwischen sehr leistungsfähige Toolkits verfügbar sind, erfordert der optimale Einsatz der KI für ein ZfP-Verfahren oftmals mehr. Die meisten Kunden möchten nicht nur eine Lösung ihres Problems; sie wollen verstehen, warum die KI so und nicht anders entschieden hat, warum der Klassifikator das Bauteil einer bestimmten Klasse (z. B. gut/schlecht oder neuwertig/verschlissen/defekt) zugewiesen hat. Abhängig von der Klassifikationsaufgabe sowie der Art und der Anzahl der vorliegenden Daten kann ein geeignetes Verfahren bestimmt werden. Mit Methoden des maschinellen Lernens werden Modelle gebildet, welche die Basis für die KI-Verfahren zur Klassifikation bilden. Der Beitrag liefert einen Überblick über KI-Verfahren und deren Anwendungen in der zerstörungsfreien Prüfung. Zahlreiche Beispiele und Ergebnisse werden vorgestellt, um die Mannigfaltigkeit des Einsatzes in der ZfP und der bestehenden Möglichkeiten zu demonstrieren. Y1 - 2017 UR - https://jt2021.dgzfp.de/portals/jt2021/bb176/inhalt/autoren.htm#T SN - 978-3-947971-18-3 ER - TY - GEN A1 - Kraljevski, Ivan A1 - Rjelka, Marek A1 - Duckhorn, Frank A1 - Tschöpe, Constanze A1 - Wolff, Matthias ED - Hillmann, Stefan ED - Weiss, Benjamin ED - Michael, Thilo ED - Möller, Sebastian T1 - Cross-Lingual Acoustic Modeling in Upper Sorbian – Preliminary Study T2 - Elektronische Sprachsignalverarbeitung 2021 : Tagungsband der 32. Konferenz Berlin, 3.-5. März 2021 N2 - In this paper, we present a preliminary study for acoustic modeling in Upper Sorbian, where a model of German was used in cross-lingual transfer learning. At first, we define the grapheme and phoneme inventories and map the target phonemes from the most similar German source equivalents. Phonetically balanced sentences for the recording prompts were selected from a combination of general and domain-specific textual data. The speech corpora with a total duration of around 11 hours was collected in controlled recording sessions involving an equal number of females, males, and children. The baseline acoustic model was employed to force-align the speech corpora given the knowledge-based phoneme mappings. How well the mappings were, was evaluated by the phoneme confusions in free-phoneme recognition. The new derived data-driven model with a reduced phoneme set was included in the adaptation and evaluation along with the baseline acoustic model. The model adaptation performance was cross-validated with the “Leave One Group Out” strategy. We observed major improvements in phoneme error rates after adaptation for the knowledge-based and data-driven phoneme mappings. The study confirmed the feasibility of transfer learning for acoustic model adaptation in the case of Upper Sorbian, at the same time demonstrating practical usability with a small vocabulary speech recognition application (Smart Lamp). Y1 - 2021 UR - https://publica.fraunhofer.de/dokumente/N-633297.html SN - 978-3-959082-27-3 SN - 0940-6832 SP - 43 EP - 50 PB - TUDpress CY - Dresden ER - TY - GEN A1 - Kraljevski, Ivan A1 - Duckhorn, Frank A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - Machine Learning for Anomaly Assessment in Sensor Networks for NDT in Aerospace T2 - IEEE Sensors Journal N2 - We investigated and compared various algorithms in machine learning for anomaly assessment with different feature analyses on ultrasonic signals recorded by sensor networks. The following methods were used and compared in anomaly detection modeling: hidden Markov models (HMM), support vector machines (SVM), isolation forest (IF), and reconstruction autoencoders (AEC). They were trained exclusively on sensor signals of the intact state of structures commonly used in various industries, like aerospace and automotive. The signals obtained on artificially introduced damage states were used for performance evaluation. Anomaly assessment was evaluated and compared using various classifiers and feature analysis methods. We introduced novel methodologies for two processes. The first was the dataset preparation with anomalies. The second was the detection and damage severity assessment utilizing the intact object state exclusively. The experiments proved that robust anomaly detection is practically feasible. We were able to train accurate classifiers which had a considerable safety margin. Precise quantitative analysis of damage severity will also be possible when calibration data become available during exploitation or by using expert knowledge. KW - Machine learning KW - Non-destructive testing KW - Ultrasonic transducers Y1 - 2021 UR - https://ieeexplore.ieee.org/document/9366491 U6 - https://doi.org/10.1109/JSEN.2021.3062941 SN - 1558-1748 VL - 21 IS - 9 SP - 11000 EP - 11008 ER - TY - GEN A1 - Kraljevski, Ivan A1 - Bissiri, Maria Paola A1 - Duckhorn, Frank A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - Glottal Stops in Upper Sorbian: A Data-Driven Approach T2 - Proc. Interspeech 2021, 30 August – 3 September, 2021, Brno, Czechia N2 - We present a data-driven approach for the quantitative analysis of glottal stops before word-initial vowels in Upper Sorbian, a West Slavic minority language spoken in Germany. Glottal stops are word-boundary markers and their detection can improve the performance of automatic speech recognition and speech synthesis systems. We employed cross-language transfer using an acoustic model in German to develop a forced-alignment method for the phonetic segmentation of a read-speech corpus in Upper Sorbian. The missing phonemic units were created by combining the existing phoneme models. In the forced-alignment procedure, the glottal stops were considered optional in front of word-initial vowels. To investigate the influence of speaker type (males, females, and children) and vowel on the occurrence of glottal stops, binomial regression analysis with a generalized linear mixed model was performed. Results show that children glottalize word-initial vowels more frequently than adults, and that glottal stop occurrences are influenced by vowel quality. Y1 - 2021 UR - https://www.isca-speech.org/archive/interspeech_2021/kraljevski21_interspeech.html U6 - https://doi.org/10.21437/Interspeech.2021-1101 SP - 1001 EP - 1005 ER - TY - GEN A1 - Kraljevski, Ivan A1 - Duckhorn, Frank A1 - Barth, Martin A1 - Tschöpe, Constanze A1 - Schubert, Frank A1 - Wolff, Matthias T1 - Autoencoder-based Ultrasonic NDT of Adhesive Bonds T2 - IEEE SENSORS 2021, Conference Proceedings, Oct 31- Nov 4, Sydney, Australia N2 - We present an approach for ultrasonic non-destructive testing of adhesive bonding employing unsupervised machine learning with autoencoders.The models are trained exclusively on the features derived from pulse-echo ultrasonic signals on a specimen with good adhesive bonding and tested on another specimen with artificially added defects.The resulting pseudo-probabilities indicating anomalies are visualized and presented along to the C-scan of the same specimen. As a result, we achieved improved representation of the defects, allowing their automatic and reliable detection. Y1 - 2021 SN - 978-1-7281-9501-8 U6 - https://doi.org/10.1109/SENSORS47087.2021.9639864 PB - IEEE ER - TY - GEN A1 - Kraljevski, Ivan A1 - Duckhorn, Frank A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - Convolutional Autoencoders for Health Indicators Extraction in Piezoelectric Sensors T2 - 2020 IEEE Sensors, 25-28 Oct. 2020, Rotterdam, Netherlands, N2 - We present a method for extracting health indicators from piezoelectric sensors applied in the case of microfluidic valves. Convolutional autoencoders were used to train a model on the normal operating conditions and tested on signals of different valves. The results of the model performance evaluation, as well as, the qualitative presentation of the indicator plots for each tested component, showed that the used approach is capable of detecting features that correspond to increasing component degradation. The extracted health indicators are the prerequisite and input for reliable remaining useful life prediction. Y1 - 2020 UR - https://ieeexplore.ieee.org/document/9323023 SN - 978-1-7281-6801-2 U6 - https://doi.org/10.1109/SENSORS47125.2020.9323023 SP - 1 EP - 4 CY - Rotterdam, Netherlands ER - TY - GEN A1 - Klimczak, Peter A1 - Kusche, Isabel A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - Menschliche und maschinelle Entscheidungsrationalität - Zur Kontrolle und Akzeptanz Künstlicher Intelligenz T2 - Zeitschrift für Medienwissenschaft 21 - Künstliche Intelligenz Y1 - 2019 UR - https://mediarep.org/handle/doc/13542 SN - 978-3-8376-4468-5 U6 - https://doi.org//10.25969/mediarep/12631 SN - 1869-1722 SN - 2296-4126 IS - 2 SP - 39 EP - 45 ER -