@misc{KraljevskiDuckhornBarthetal., author = {Kraljevski, Ivan and Duckhorn, Frank and Barth, Martin and Tsch{\"o}pe, Constanze and Schubert, Frank and Wolff, Matthias}, title = {Autoencoder-based Ultrasonic NDT of Adhesive Bonds}, series = {IEEE SENSORS 2021, Conference Proceedings, Oct 31- Nov 4, Sydney, Australia}, journal = {IEEE SENSORS 2021, Conference Proceedings, Oct 31- Nov 4, Sydney, Australia}, publisher = {IEEE}, isbn = {978-1-7281-9501-8}, doi = {10.1109/SENSORS47087.2021.9639864}, pages = {4}, abstract = {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.}, language = {en} } @misc{KraljevskiDuckhornTschoepeetal., author = {Kraljevski, Ivan and Duckhorn, Frank and Tsch{\"o}pe, Constanze and Schubert, Frank and Wolff, Matthias}, title = {Paper Tissue Softness Rating by Acoustic Emission Analysis}, series = {Applied Sciences}, volume = {13}, journal = {Applied Sciences}, number = {3}, issn = {2076-3417}, doi = {10.3390/app13031670}, abstract = {Softness is one of the essential properties of hygiene tissue products. Reliably measuring it is of utmost importance to ensure the balance between customer expectations and cost-effective tissue production. This study presents a method for assessing softness by analyzing acoustic emissions produced while tearing a tissue specimen. The aim was to train neural network models using the corrected results of human panel tests as the ground truth labels and to predict the tissue softness in two- and three-class recognition tasks. We also investigate the possibility of predicting some production parameters related to the softness property. The results proved that tissue softness and production parameters could be reliably estimated only by the tearing noise.}, language = {en} } @misc{DuckhornWolffHoffmann, author = {Duckhorn, Frank and Wolff, Matthias and Hoffmann, R{\"u}diger}, title = {A new Epsilon Filter for Efficient Composition of Weighted Finite-State Transducers}, series = {Interspeech 2011, 12th annual conference of the International Speech Communication Association 2011, Florence, Italy, 27 - 31 August 2011}, journal = {Interspeech 2011, 12th annual conference of the International Speech Communication Association 2011, Florence, Italy, 27 - 31 August 2011}, publisher = {ISCA}, pages = {897 -- 900}, language = {en} } @inproceedings{DuckhornWolffHoffmann, author = {Duckhorn, Frank and Wolff, Matthias and Hoffmann, R{\"u}diger}, title = {Realisierung von Mischverteilungsdichten durch gewichtete endliche Automaten (Finite-State Transducers)}, language = {de} } @inproceedings{DuckhornStrechaWolffetal., author = {Duckhorn, Frank and Strecha, Guntram and Wolff, Matthias and Hoffmann, R{\"u}diger}, title = {Entwicklung und Performance eines Sprachdialogsystems mit begrenzten Hardwareressourcen}, language = {de} } @inproceedings{DuckhornStrechaWolffetal., author = {Duckhorn, Frank and Strecha, Guntram and Wolff, Matthias and Hoffmann, R{\"u}diger}, title = {Ein Sprachdialogsystem mit begrenzten Hardwareressourcen}, series = {Elektronische Sprachsignalverarbeitung 2009, Tagungsband der 20. Konferenz, Dresden, 21. bis 23. September 2009, Band 1}, booktitle = {Elektronische Sprachsignalverarbeitung 2009, Tagungsband der 20. Konferenz, Dresden, 21. bis 23. September 2009, Band 1}, editor = {Hoffmann, R{\"u}diger}, publisher = {TUDpress}, address = {Dresden}, isbn = {978-3-941298-31-6}, pages = {88 -- 93}, language = {de} } @inproceedings{KraljevskiDuckhornWolffetal., author = {Kraljevski, Ivan and Duckhorn, Frank and Wolff, Matthias and Hoffmann, R{\"u}diger}, title = {Multi-condition training and adaptation for noise robust speech recognition}, series = {Elektronische Sprachsignalverarbeitung 2012, Tagungsband der 23. Konferenz, Cottbus, 29. - 31. August 2012}, booktitle = {Elektronische Sprachsignalverarbeitung 2012, Tagungsband der 23. Konferenz, Cottbus, 29. - 31. August 2012}, editor = {Wolff, Matthias}, isbn = {978-3-942710-81-7}, pages = {73 -- 80}, language = {en} } @inproceedings{TschoepeWolffStrechaetal., author = {Tsch{\"o}pe, Constanze and Wolff, Matthias and Strecha, Guntram and Duckhorn, Frank and Feher, Thomas and Hoffmann, R{\"u}diger}, title = {Automatisierte Weichheitspr{\"u}fung von Papier}, series = {ZfP in Forschung, Entwicklung und Anwendung, Graz, 17. - 19. September 2012, DACH-Jahrestagung 2012 Zerst{\"o}rungsfreie Materialpr{\"u}fung}, booktitle = {ZfP in Forschung, Entwicklung und Anwendung, Graz, 17. - 19. September 2012, DACH-Jahrestagung 2012 Zerst{\"o}rungsfreie Materialpr{\"u}fung}, publisher = {DGZfP}, address = {Berlin}, isbn = {978-394-02834-4-3}, language = {de} } @techreport{DuckhornWolffTschoepe, author = {Duckhorn, Frank and Wolff, Matthias and Tsch{\"o}pe, Constanze}, title = {Hidden Markov Model training using Finite State Machines}, publisher = {Technische Universit{\"a}t, Institut f{\"u}r Akustik und Sprachkommunikation}, address = {Dresden}, language = {de} } @inproceedings{DuckhornWolffStrechaetal., author = {Duckhorn, Frank and Wolff, Matthias and Strecha, Guntram and Hoffmann, R{\"u}diger}, title = {An application example for unified speech synthesis and recognition using Hidden Markov Models}, series = {One day meeting on unified models for speech recognition and synthesis, Birmingham, U.K. March 2009}, booktitle = {One day meeting on unified models for speech recognition and synthesis, Birmingham, U.K. March 2009}, doi = {10.13140/RG.2.1.1626.8969}, language = {en} } @inproceedings{TschoepeJoneitDuckhornetal., author = {Tsch{\"o}pe, Constanze and Joneit, Dieter and Duckhorn, Frank and Strecha, Guntram and Hoffmann, R{\"u}diger and Wolff, Matthias}, title = {Voice control for measurement devices}, series = {AIA-DAGA 2013, proceedings of the International Conference on Acoustics , 18 - 21 March 2013 in Merano}, booktitle = {AIA-DAGA 2013, proceedings of the International Conference on Acoustics , 18 - 21 March 2013 in Merano}, publisher = {DEGA}, address = {Berlin}, language = {en} } @inproceedings{HusseinWolffJokischetal., author = {Hussein, Hussein and Wolff, Matthias and Jokisch, Oliver and Duckhorn, Frank and Strecha, Guntram and Hoffmann, R{\"u}diger}, title = {A hybrid speech signal based algorithm for pitch marking using finite state machines}, series = {9th annual conference of the International Speech Communication Association 2008 (INTERSPEECH 2008), Brisbane, Australia, 22 - 26 September 2008, Vol. 1}, booktitle = {9th annual conference of the International Speech Communication Association 2008 (INTERSPEECH 2008), Brisbane, Australia, 22 - 26 September 2008, Vol. 1}, publisher = {Curran}, address = {Red Hook, NY}, isbn = {978-1-61567-378-0}, pages = {135 -- 138}, language = {en} } @inproceedings{TschoepeDuckhornBluethgenetal., author = {Tsch{\"o}pe, Constanze and Duckhorn, Frank and Bl{\"u}thgen, Peter and Richter, Christian and Papsdorf, Gunther and Wolff, Matthias}, title = {Miniaturisiertes System zur intelligenten Signalverarbeitung}, series = {DGZFP-Jahrestagung 2017, Zerst{\"o}rungsfreie Materialpr{\"u}fung, Koblenz, 22.-24.05.2017, Kurzfassungen der Vortr{\"a}ge und Posterbeitr{\"a}ge}, booktitle = {DGZFP-Jahrestagung 2017, Zerst{\"o}rungsfreie Materialpr{\"u}fung, Koblenz, 22.-24.05.2017, Kurzfassungen der Vortr{\"a}ge und Posterbeitr{\"a}ge}, publisher = {DGZIP}, address = {Berlin}, pages = {S. 192}, language = {de} } @techreport{TschoepeDuckhornWolff, author = {Tsch{\"o}pe, Constanze and Duckhorn, Frank and Wolff, Matthias}, title = {Akustische Mustererkennung: Qualit{\"a}tskontrolle - Vorausschauende Instandhaltung - Zustands{\"u}berwachung}, publisher = {Fraunhofer-IKTS}, address = {Dresden}, pages = {6}, language = {de} } @misc{TschoepeKraljevskiDuckhornetal., author = {Tsch{\"o}pe, Constanze and Kraljevski, Ivan and Duckhorn, Frank and Wolff, Matthias}, title = {Sprachtechnologie und akustische Mustererkennung in der medizinischen Anwendung}, series = {16. Landeskonferenz „Digitalisierung im Gesundheitswesen" 2021}, journal = {16. Landeskonferenz „Digitalisierung im Gesundheitswesen" 2021}, pages = {9}, language = {de} } @misc{WunderlichTschoepeDuckhorn, author = {Wunderlich, Christian and Tsch{\"o}pe, Constanze and Duckhorn, Frank}, title = {Advanced methods in NDE using machine learning approaches}, series = {44th Annual Review of Progress in Quantitative Nondestructive Evaluation, Provo, Utah, USA, 16-21 July 2017}, volume = {37}, journal = {44th Annual Review of Progress in Quantitative Nondestructive Evaluation, Provo, Utah, USA, 16-21 July 2017}, publisher = {AIP Publishing}, address = {College Park, Maryland}, issn = {0094-243X}, doi = {10.1063/1.5031519}, pages = {1 -- 8}, abstract = {Machine learning (ML) methods and algorithms have been applied recently with great success in quality control and predictive maintenance. Its goal to build new and/or leverage existing algorithms to learn from training data and give accurate predictions, or to find patterns, particularly with new and unseen similar data, fits perfectly to Non-Destructive Evaluation. The advantages of ML in NDE are obvious in such tasks as pattern recognition in acoustic signals or automated processing of images from X-ray, Ultrasonics or optical methods. Fraunhofer IKTS is using machine learning algorithms in acoustic signal analysis. The approach had been applied to such a variety of tasks in quality assessment. The principal approach is based on acoustic signal processing with a primary and secondary analysis step followed by a cognitive system to create model data. Already in the second analysis steps unsupervised learning algorithms as principal component analysis are used to simplify data structures. In the cognitive part of the software further unsupervised and supervised learning algorithms will be trained. Later the sensor signals from unknown samples can be recognized and classified automatically by the algorithms trained before. Recently the IKTS team was able to transfer the software for signal processing and pattern recognition to a small printed circuit board (PCB). Still, algorithms will be trained on an ordinary PC; however, trained algorithms run on the Digital Signal Processor and the FPGA chip. The identical approach will be used for pattern recognition in image analysis of OCT pictures. Some key requirements have to be fulfilled, however. A sufficiently large set of training data, a high signal-to-noise ratio, and an optimized and exact fixation of components are required. The automated testing can be done subsequently by the machine. By integrating the test data of many components along the value chain further optimization including lifetime and durability prediction based on big data becomes possible, even if components are used in different versions or configurations. This is the promise behind German Industry 4.0.}, language = {en} } @inproceedings{StrechaWolffDuckhornetal., author = {Strecha, Guntram and Wolff, Matthias and Duckhorn, Frank and Wittenberg, S{\"o}ren and Tsch{\"o}pe, Constanze}, title = {The HMM synthesis algorithm of an embedded unified speech recognizer and synthesizer}, series = {Proceedings of the Annual Conference of the International Speech Communication Association 2009, Interspeech 2009, 6 - 10 September, 2009, Brighton, UK}, booktitle = {Proceedings of the Annual Conference of the International Speech Communication Association 2009, Interspeech 2009, 6 - 10 September, 2009, Brighton, UK}, publisher = {ISCA}, address = {Brighton}, pages = {1763 -- 1766}, language = {en} } @misc{SchmidtHildebrandKraljevskietal., author = {Schmidt, Ralph Rudi and Hildebrand, Jorg and Kraljevski, Ivan and Duckhorn, Frank and Tsch{\"o}pe, Constanze}, title = {A study for laser additive manufacturing quality and material classification using machine learning}, series = {2022 IEEE sensors}, journal = {2022 IEEE sensors}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, address = {Piscataway, New Jersey}, isbn = {978-1-6654-8464-0}, issn = {2168-9229}, doi = {10.1109/SENSORS52175.2022.9967311}, pages = {1 -- 4}, abstract = {This paper demonstrates the use of acoustic emissions (AEs) to monitor the quality, and material used, for the laser additive manufacturing (LAM) process with steel and copper wire. Layers of deposited material (steel or copper) were created using LAM. The quality of these layers was either good or unstable. The AEs were recorded using three sensors, one microphone, and two structure-borne sound probes. The recorded signals were processed and transformed using the fast Fourier method. Then models were trained with the processed data and evaluated using a fivefold cross-validation. Results show that it is possible to accurately classify the materials used during LAM (up to a balanced accuracy [BAcc] score of 0.99). Also, the process quality could be classified with a BAcc score of up to 0.81. Overall, the results are promising, but further research and data collection are necessary for a proper validation of our results.}, language = {en} } @misc{OpitzWunderlichBendjusetal., author = {Opitz, Joerg and Wunderlich, Christian and Bendjus, B. and Cikalova, U. and Wolf, C. and Naumann, S. and Lehmann, A. and Barth, M. and Duckhorn, Frank and K{\"o}hler, B. and Tsch{\"o}ke, K. and Windisch, T. and Tsch{\"o}pe, Constanze and Moritz, T. and Scheithauer, U.}, title = {Materialdiagnose und integrale Pr{\"u}fverfahren f{\"u}r keramische Bauteile}, series = {Keramische Zeitschrift}, volume = {68}, journal = {Keramische Zeitschrift}, number = {4-5}, publisher = {Springer Science and Business Media LLC}, address = {Berlin ; Heidelberg}, issn = {0023-0561}, doi = {10.1007/BF03400267}, pages = {249 -- 254}, abstract = {Hochleistungskeramiken findet man heute h{\"a}ufig als kritische Komponente in neuentwickelten Systemen f{\"u}r Zukunftsanwendungen. Die Zuverl{\"a}ssigkeit des gesamten Systems basiert hierbei oft auf der kritischen keramischen Komponente. F{\"u}r diese oft neuentwickelten keramischen Materialien werden neue Methoden f{\"u}r die Prozesssteuerung, Materialdiagnostik und Struktur{\"u}berwachung ben{\"o}tigt. In diesem Artikel werden drei f{\"u}r die Keramikcharakterisierung am Fraunhofer-Institut f{\"u}r Keramische Technologien und Systeme IKTS weiter entwickelte Technologien und Verfahren beschrieben und deren Einsatz anhand von Beispielen illustriert. Dazu werden die Laser-Speckle-Photometrie, die optische Koh{\"a}renztomographie und die Klanganalyse in Kombination mit einer entsprechenden akustischen Mustererkennung als leistungsf{\"a}hige Verfahren f{\"u}r die Materialdiagnostik im Bereich der keramischen Materialien vorgestellt.}, language = {de} } @misc{KraljevskiDuckhornSobeetal., author = {Kraljevski, Ivan and Duckhorn, Frank and Sobe, Daniel and Tsch{\"o}pe, Constanze and Wolff, Matthias}, title = {Speech-to-text in upper sorbian : current state}, series = {Elektronische Sprachsignalverarbeitung 2025 : Tagungsband der 36. Konferenz Halle/Saale, 5.-7. M{\"a}rz 2025}, journal = {Elektronische Sprachsignalverarbeitung 2025 : Tagungsband der 36. Konferenz Halle/Saale, 5.-7. M{\"a}rz 2025}, editor = {Grawunder, Sven}, publisher = {TUDpress}, address = {Dresden}, isbn = {978-3-95908-803-9}, issn = {0940-6832}, pages = {109 -- 116}, abstract = {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.}, language = {en} } @misc{KraljevskiDuckhornSobeetal., author = {Kraljevski, Ivan and Duckhorn, Frank and Sobe, Daniel and Tsch{\"o}pe, Constanze and Wolff, Matthias}, title = {Preserving Language Heritage Through Speech Technology: The Case of Upper Sorbian}, series = {Speech and Computer, SPECOM 2024, Belgrade, Serbia, 25-28 November 2024}, journal = {Speech and Computer, SPECOM 2024, Belgrade, Serbia, 25-28 November 2024}, editor = {Karpov, Alexey and Delic, Vlado}, publisher = {Springer Nature Switzerland, Cham}, isbn = {978-3-031-77960-2}, doi = {10.1007/978-3-031-77961-9_1}, pages = {3 -- 22}, abstract = {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.}, language = {en} }