TY - GEN A1 - Duckhorn, Frank A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger T1 - A new Epsilon Filter for Efficient Composition of Weighted Finite-State Transducers T2 - Interspeech 2011, 12th annual conference of the International Speech Communication Association 2011, Florence, Italy, 27 - 31 August 2011 Y1 - 2011 UR - https://www.isca-speech.org/archive/archive_papers/interspeech_2011/i11_0897.pdf SP - 897 EP - 900 PB - ISCA ER - TY - CHAP A1 - Strecha, Guntram A1 - Wolff, Matthias T1 - Speech synthesis using HMM based diphone inventory encoding for low-resource devices T2 - 2011 IEEE International Conference on Acoustics, Speech and Signal Processing, (ICASSP 2011), Prague, Czech Republic, 22 - 27 May 2011 Y1 - 2011 SN - 978-1-457-70538-0 U6 - https://doi.org/10.1109/ICASSP.2011.5947574 SP - 5380 EP - 5383 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger ED - Esposito, Anna T1 - An Approach to Intelligent Signal Processing T2 - Behavioral Cognitive Systems Y1 - 2012 SP - 1 EP - 18 PB - Springer CY - Berlin [u.a.] ER - TY - CHAP A1 - Paessler, Sebastian A1 - Wolff, Matthias A1 - Fischer, Wolf-Joachim T1 - Chewing sound classification using a grammar based classification algorithm T2 - Proceedings of Forum Acusticum 2011, 27 June - 01 July, Aalborg, Denmark Y1 - 2011 SN - 978-84-694-1520-7 SP - 39 EP - 44 PB - Spanish Acoustical Society CY - Madrid ER - TY - CHAP A1 - Paessler, Sebastian A1 - Wolff, Matthias A1 - Fischer, Wolf-Joachim T1 - Chewing Sound Classification Using Algorithms of Speech Recognition Y1 - 2011 ER - TY - CHAP A1 - Paessler, Sebastian A1 - Fischer, Wolf-Joachim A1 - Wolff, Matthias T1 - Food Intake Recognition Conception for Wearable Devices T2 - MobileHealth '11, Proceedings of the First ACM MobiHoc Workshop on Pervasive Wireless Healthcare, Paris, FR, May 2011 Y1 - 2011 SN - 978-1-4503-0780-2 SP - 1 EP - 4 PB - ACM CY - New York ER - TY - GEN A1 - Päßler, Sebastian A1 - Wolff, Matthias A1 - Fischer, Wolf-Joachim T1 - Food intake monitoring: An acoustical approach to automated food intake activity detection and classification of consumed food T2 - Physiological Measurement Y1 - 2012 UR - http://iopscience.iop.org/0967-3334/33/6/1073/pdf/0967-3334_33_6_1073.pdf SN - 1361-6579 VL - 33 IS - 6 SP - 1073 EP - 1093 ER - TY - CHAP A1 - Hoffmann, Rüdiger A1 - Wolff, Matthias T1 - Towards hierarchical cognitive systems for intelligent signal processing T2 - ICT Innovations 2012, Secure and Intelligent Systems, Ohrid, Macedonia, Sep. 2012, WEB proceedings Y1 - 2012 SN - 1857-7288 SP - 613 EP - 618 PB - ICT ACT ER - TY - CHAP A1 - Kraljevski, Ivan A1 - Strecha, Guntram A1 - Wolff, Matthias A1 - Jokisch, Oliver A1 - Chungurski, Slavcho A1 - Hoffmann, Rüdiger ED - Markovski, Smile ED - Gushev, Marjan T1 - Cross-language acoustic modeling for Macedonian speech technology applications T2 - ICT Innovations 2012, Secure and Intelligent Systems Y1 - 2013 UR - http://link.springer.com/chapter/10.1007%2F978-3-642-37169-1_4 SN - 978-3-642-37168-4 U6 - https://doi.org/10.1007/978-3-642-37169-1_4 SP - 35 EP - 45 PB - Springer CY - Berlin [u.a.] ER - TY - CHAP A1 - Kraljevski, Ivan A1 - Duckhorn, Frank A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger ED - Wolff, Matthias T1 - Multi-condition training and adaptation for noise robust speech recognition T2 - Elektronische Sprachsignalverarbeitung 2012, Tagungsband der 23. Konferenz, Cottbus, 29. - 31. August 2012 Y1 - 2012 SN - 978-3-942710-81-7 SP - 73 EP - 80 ER - TY - CHAP A1 - Kraljevski, Ivan A1 - Strecha, Guntram A1 - Wolff, Matthias A1 - Jokisch, Oliver A1 - Hoffmann, Rüdiger T1 - Using unified automatic speech recognition and synthesis system for cross-language acoustic modeling T2 - Proceedings Digitalna Obrada Govora I Slike (DOGS 2012) Y1 - 2012 SN - 978-86-7892-439-2 SP - 4 EP - 11 CY - Kovacica, Serbia ER - TY - CHAP A1 - Duckhorn, Frank A1 - Wolff, Matthias A1 - Strecha, Guntram A1 - Hoffmann, Rüdiger T1 - An application example for unified speech synthesis and recognition using Hidden Markov Models T2 - One day meeting on unified models for speech recognition and synthesis, Birmingham, U.K. March 2009 Y1 - 2009 U6 - https://doi.org/10.13140/RG.2.1.1626.8969 ER - TY - CHAP A1 - Tschöpe, Constanze A1 - Joneit, Dieter A1 - Duckhorn, Frank A1 - Strecha, Guntram A1 - Hoffmann, Rüdiger A1 - Wolff, Matthias T1 - Voice control for measurement devices T2 - AIA-DAGA 2013, proceedings of the International Conference on Acoustics , 18 - 21 March 2013 in Merano Y1 - 2013 PB - DEGA CY - Berlin ER - TY - CHAP A1 - Hoffmann, Rüdiger A1 - Eichner, Matthias A1 - Wolff, Matthias ED - Esposito, Anna ED - Faundez-Zanuy, Marcos ED - Keller, Eric ED - Marinaro, Maria T1 - Analysis of verbal and nonverbal acoustic signals with the Dresden UASR system T2 - Verbal and Nonverbal Communication Behaviours Y1 - 2007 SN - 978-3-540-76441-0 SP - 200 EP - 218 PB - Springer CY - Berlin [u.a.] ER - TY - CHAP A1 - Hussein, Hussein A1 - Wolff, Matthias A1 - Jokisch, Oliver A1 - Duckhorn, Frank A1 - Strecha, Guntram A1 - Hoffmann, Rüdiger T1 - A hybrid speech signal based algorithm for pitch marking using finite state machines T2 - 9th annual conference of the International Speech Communication Association 2008 (INTERSPEECH 2008), Brisbane, Australia, 22 - 26 September 2008, Vol. 1 Y1 - 2008 SN - 978-1-61567-378-0 SP - 135 EP - 138 PB - Curran CY - Red Hook, NY ER - TY - CHAP A1 - Wittenberg, Sören A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger T1 - Feasibility of statistical classifiers for monitoring rollers T2 - International Conference on Signals and Electronic Systems (ICSES 08), Krakow, 14. - 17. 9. 2008 Y1 - 2008 U6 - https://doi.org/10.1109/ICSES.2008.4673468 SP - 463 EP - 466 PB - IEEE ER - TY - CHAP A1 - Eichner, Matthias A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger T1 - An HMM Based Investigation of Differences Between Musical Instruments of the Same Type T2 - 19th International Congress on Acoustics (ICA 2007), Madrid, Spain, September 2-7, 2007 Y1 - 2007 SN - 84-87985-12-2 CY - Madrid ER - TY - CHAP A1 - Petrick, Rico A1 - Lohde, Kevin A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger T1 - The harming part of room acoustics in automatic speech recognition T2 - 8th annual conference of the International Speech Communication Association, Interspeech 2007, August 27 - 31, 2007, Antwerp, Belgium Y1 - 2007 SP - 1094 EP - 1097 ER - TY - CHAP A1 - Wolff, Matthias A1 - Kordon, Ulrich A1 - Hussein, Hussein A1 - Eichner, Matthias A1 - Tschöpe, Constanze A1 - Hoffmann, Rüdiger T1 - Auscultatory blood pressure measurement using HMMs T2 - IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Honolulu, Hawaii, April 15-20, 2007 Y1 - 2007 U6 - https://doi.org/10.1109/ICASSP.2007.366702 SP - I-405 EP - I-408 PB - IEEE ER - TY - CHAP A1 - Eichner, Matthias A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger ED - Wahlster, Wolfgang T1 - Data driven generation of pronunciation dictionaries T2 - Verbmobil - Foundations of speech-to-speech translation Y1 - 2000 SN - 978-3-662-04230-4 SP - 95 EP - 105 PB - Springer CY - Berlin [u.a.] ER - TY - CHAP A1 - Eichner, Matthias A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger T1 - A framework for internet-based tutorials on spoken language engineering T2 - Proceedings, 2000 IEEE International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2000, Honolulu, Hawaii, Nov. 5 - 8, 2000, vol. 2 Y1 - 2000 SP - 722 EP - 726 PB - IEEE ER - TY - CHAP A1 - Hoffmann, Rüdiger A1 - Wolff, Matthias T1 - Framework design and implementation of web-based tutorials in spoken language engineering T2 - Proceedings, IEEE International Conference on Multimedia and Expo, ICME 2000, 30 July - 2 August 2000, New York, NY, USA, Vol. 2 Y1 - 2000 SN - 0-7803-6536-4 U6 - https://doi.org/10.1109/ICME.2000.871471 SP - 755 EP - 758 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Eichner, Matthias A1 - Wolff, Matthias T1 - Data-driven generation of pronunciation dictionaries in the German Verbmobil project - Discussion of experimental results T2 - Proceedings, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2000), Istanbul, 5 - 9 June, 2000, vol. 3 Y1 - 2000 SN - 0-7803-6293-4 U6 - https://doi.org/10.1109/ICASSP.2000.862075 SP - 1687 EP - 1690 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Flach, G. A1 - Holzapfel, M. A1 - Just, C. A1 - Wachtler, A. A1 - Wolff, Matthias T1 - Automatic learning of numeral grammars for multi-lingual speech synthesizers T2 - Proceedings, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2000), Istanbul, 5 - 9 June, 2000, vol. 3 Y1 - 2000 U6 - https://doi.org/10.1109/ICASSP.2000.861814 SP - 1291 EP - 1294 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Eichner, Matthias A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger T1 - Instrument classification using Hidden Markov Models T2 - ISMIR 2006, 7th International Conference on Music Information Retrieval, Victoria, 8. - 12. 10. 2006, Proceedings Y1 - 2006 SN - 978-1-55058-349-6 SP - 349 EP - 350 PB - Univ. of Victoria CY - Victoria ER - TY - CHAP A1 - Werner, Steffen A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger T1 - Pronunciation variant selection for spontaneous speech synthesis - Listening effort as a quality parameter T2 - IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006, 14 - 19 May 2006, Toulouse, France, Proceedings, Vol. 1 Y1 - 2006 U6 - https://doi.org/10.1109/ICASSP.2006.1660156 SP - 857 EP - 860 PB - IEEE Operations Center CY - Piscataway, NJ ER - TY - CHAP A1 - Kühne, Marco A1 - Wolff, Matthias A1 - Eichner, Matthias A1 - Hoffmann, Rüdiger T1 - Voice activation using prosodic features T2 - Proceedings, 8th International Convention Center Jeju, Jeju Island, Korea, October 4 - 8, 2004, vol. 4 Y1 - 2004 SP - 3001 EP - 3004 ER - TY - CHAP A1 - Werner, Steffen A1 - Wolff, Matthias A1 - Eichner, Matthias A1 - Hoffmann, Rüdiger T1 - Integrating speech enabled services in a web-based e-learning environment T2 - Proceedings, ITCC 2004, International Conference on Information Technology: Coding and Computing, April 5 - 7, 2004, Las Vegas, Nevada, vol. 2 Y1 - 2004 U6 - https://doi.org/10.1109/ITCC.2004.1286651 SP - 303 EP - 307 PB - IEEE Computer Society CY - Los Alamitos, Calif. [u.a.] ER - TY - CHAP A1 - Werner, Steffen A1 - Wolff, Matthias A1 - Eichner, Matthias A1 - Hoffmann, Rüdiger T1 - Modeling pronunciation variation for spontaneous speech synthesis T2 - IEEE International Conference on Acoustics, Speech, and Signal Processing,(ICASSP '04), May 17 - 21, 2004, Montreal, Canada Y1 - 2004 SN - 0-7803-8484-9 U6 - https://doi.org/10.1109/ICASSP.2004.1326075 SP - I-673 EP - I-676 PB - IEEE ER - TY - CHAP A1 - Eichner, Matthias A1 - Göcks, Marc-Steffen A1 - Hoffmann, Rüdiger A1 - Wolff, Matthias T1 - Speech enabled services in a web-based e-learning environment T2 - Proceedings of the IASTED International Conference on Web-Based Education, February 16 - 18, 2004, Innsbruck, Austria Y1 - 2004 SN - 0-88986-406-3 SP - 157 EP - 162 PB - Acta Press CY - Anaheim [u.a.] ER - TY - CHAP A1 - Eichner, Matthias A1 - Werner, Steffen A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger T1 - Towards spontaneous speech synthesis: LM based selection of pronunciation variants T2 - IEEE International Conference on Acoustics, Speech, and Signal Processing, April 6 - 10, 2003, Hong Kong, proceedings, Vol. 1 Y1 - 2003 SN - 0-7803-7663-3 U6 - https://doi.org/10.1109/ICASSP.2003.1198764 SP - 248 EP - 251 PB - IEEE Operations Center CY - Piscataway, NJ ER - TY - CHAP A1 - Hoffmann, Rüdiger A1 - Eichner, Matthias A1 - Werner, Steffen A1 - Wolff, Matthias T1 - The Project UASR (Unified Approach for Speech Synthesis and Recognition) - A Progress Report T2 - Proceedings of the Speech Processing Workshop, Magdeburg, Germany, September 09, DAGM 2003 Y1 - 2003 SP - 17 EP - 24 CY - Magdeburg ER - TY - CHAP A1 - Eichner, Matthias A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger T1 - Improved Duration Control for Speech Synthesis Using a Multigram Language Model T2 - IEEE Internatinal Conference on Acoustics, Speech, and Signal Processing (ICASSP 2002), May 13-17, Orlando, FL, Vol. 1 Y1 - 2002 U6 - https://doi.org/10.1109/ICASSP.2002.5743743 SP - 417 EP - 420 PB - IEEE ER - TY - CHAP A1 - Wolff, Matthias A1 - Eichner, Matthias A1 - Hoffmann, Rüdiger T1 - Measuring the Quality of Pronunciation Dictionaries T2 - PMLA 2002, ISCA Workshop on Pronunciation Modeling and Lexicon Adaptation for Spoken Language, September 14 - 15, Estes Park, CO Y1 - 2002 SP - 117 EP - 122 ER - TY - CHAP A1 - Eichner, Matthias A1 - Wolff, Matthias A1 - Ohnewald, Sebastian A1 - Hoffmann, Rüdiger T1 - Speech synthesis using stochastic Markov graphs T2 - Proceedings, International Conference on Acoustics, Speech and Signal Processing, 7 - 11 May 2001, Salt Palace Convention Center, Salt Lake City, Utah, USA Y1 - 2001 SN - 0-7803-7041-4 U6 - https://doi.org/10.1109/ICASSP.2001.941043 SP - 829 EP - 832 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Wolff, Matthias A1 - Eichner, Matthias A1 - Hoffmann, Rüdiger T1 - Improved data-driven generation of pronunciation dictionaries using an adapted word list T2 - Proceedings, Eurospeech 2001, Scandinavia, 7th European Conference on Speech Communication and Technology, September 3 - 7, 2001, Aalborg, vol. 3 Y1 - 2001 SN - 87-90834-09-7 SP - 1433 EP - 1436 CY - Aalborg ER - TY - CHAP A1 - Wolff, Matthias A1 - Eichner, Matthias A1 - Hoffmann, Rüdiger T1 - Automatic learning and optimization of pronunciation dictionaries T2 - Proceedings of the Workshop Adaptation Methods for Speech Recognition, Sophia-Antipolis, France, August 29 - 30, 2001, Isca ITR-workshop Y1 - 2001 SP - 159 EP - 162 CY - Sophia-Antipolis ER - TY - CHAP A1 - Werner, Steffen A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger ED - Vich, Robert T1 - Pronunciation variation modeling for spontaneous speech synthesis T2 - Electronic speech signal processing, proceedings of the 16th conference joined with the 15th Czech-German Workshop "Speech Processing", Prague, September 26 - 28, 2005 Y1 - 2005 SN - 3-938863-17-X SP - 381 EP - 387 PB - TUDpress CY - Dresden ER - TY - CHAP A1 - Wolff, Matthias A1 - Eichner, Matthias A1 - Estelmann, J. A1 - Werner, Steffen A1 - Hoffmann, Rüdiger ED - Vich, Robert T1 - Meta-classification for a language identification task T2 - Electronic speech signal processing, proceedings of the 16th conference joined with the 15th Czech-German Workshop "Speech Processing", Prague, September 26 - 28, 2005 Y1 - 2005 SN - 3-938863-17-X SN - 978-3-938863-17-6 SP - 346 EP - 355 PB - TUDpress CY - Dresden ER - TY - CHAP A1 - Werner, Steffen A1 - Wolff, Matthias A1 - Eichner, Matthias A1 - Estelmann, J. A1 - Hoffmann, Rüdiger T1 - Language identification using meta-classification of multiple experts T2 - Proceedings, 10th International Conference Speech and Computer, 17 - 19 October 2005, Patras, Greece, SPECOM 2005, vol. 2 Y1 - 2005 SP - 519 EP - 522 ER - TY - GEN A1 - Eichner, Matthias A1 - Göcks, Marc-Steffen A1 - Hoffmann, Rüdiger A1 - Kühne, Matthias A1 - Wolff, Matthias T1 - Speech-enabled services in a web-based e-learning environment T2 - Advanced Technology for Learning Y1 - 2004 SN - 1710-2251 VL - 1 IS - 2 SP - 91 EP - 98 ER - TY - GEN A1 - Werner, Steffen A1 - Eichner, Matthias A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger T1 - Towards spontaneous speech synthesis - Utilizing language model information in TTS T2 - IEEE transactions on speech and audio processing Y1 - 2004 U6 - https://doi.org/10.1109/TSA.2004.828635 SN - 1063-6676 VL - 12 IS - 4 SP - 436 EP - 445 ER - TY - CHAP A1 - Eichner, Matthias A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger T1 - Voice characteristics conversion for TTS using reverse VTLN T2 - Proceedings IEEE International Conference on Acoustics, Speech, and Signal Processing, (ICASSP), May 17 - 21, 2004, Montreal, Canada Y1 - 2004 U6 - https://doi.org/10.1109/ICASSP.2004.1325911 SP - I-17 EP - I-20 PB - IEEE ER - TY - CHAP A1 - Wolff, Matthias ED - Höge, Harald ED - Horvat, Bogomir ED - Kačič, Zdravko T1 - On representation and training of pronunciation dictionaries T2 - Advances in speech technology, recent progress in speech technology, proceedings, sixth international workshop, Munich, Germany, July 8-9, 1999 Y1 - 1999 SN - 86-435-0335-5 SP - 175 EP - 190 ER - TY - CHAP A1 - Eichner, Matthias A1 - Wolff, Matthias A1 - Hoffmann, Rüdiger T1 - A unified approach for speech synthesis and speech recognition using Stochastic Markov Graphs T2 - The proceedings of the conference, ICSLP 2000, Oct. 16 - Oct. 20, 2000, Beijing International Convention Center, Beijing, China, Vol. 1 Y1 - 2000 SN - 7-80150-114-4 SP - 701 EP - 704 CY - Beijing ER - TY - CHAP A1 - Hirschfeld, Diane A1 - Wolff, Matthias T1 - Universal and multilingual unit selection for DreSS T2 - The proceedings of the conference, ICSLP 2000, Oct. 16 - Oct. 20, 2000, Beijing International Convention Center, Beijing, China, Vol. 1 Y1 - 2000 SN - 7-80150-114-4 SP - 717 EP - 720 CY - Beijing ER - TY - CHAP A1 - Wolff, Matthias ED - Vich, Robert T1 - On representation and training of pronunciation dictionaries T2 - 8th Czech-German Workshop Speech Processing, Prague, Czech Republic, 14th -16th September 1998 Y1 - 1998 SN - 80-86269-00-0 PB - Institute of Radio Engineering and Electronics CY - Prague ER - TY - CHAP A1 - Wolff, Matthias A1 - Römer, Ronald A1 - Wirsching, Günther T1 - Towards coping and imagination for cognitive agents T2 - 6th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), Györ (Hungary), October 9-21, 2015 Y1 - 2015 U6 - https://doi.org/10.1109/CogInfoCom.2015.7390609 SP - 307 EP - 312 PB - IEEE ER - TY - CHAP A1 - Huber, Markus A1 - Römer, Ronald A1 - Wolff, Matthias ED - Trouvain, Jürgen ED - Steiner, Ingmar ED - Möbius, Bernd T1 - Little Drop of Mulligatawny Soup, Miss Sophie? Automatic Speech Understanding provided by Petri Nets T2 - Tagungsband der 28. Konferenz Elektronische Sprachsignalverarbeitung (ESSV), 15.-17.03.2017, Saarbrücken Y1 - 2017 SN - 978-3-95908-094-1 SP - 122 EP - 129 PB - TUDpress CY - Dresden ER - TY - CHAP A1 - Huber, Markus A1 - Wolff, Matthias ED - Aalst, Wil van der ED - Bergenthum, Robin ED - Carmona, Josep T1 - Segmenting Sequences Semantically. Using Petri Net Transducers for the Translation from Sequential Data to Non-Sequential Models T2 - Proceedings of the International Workshop on Algorithms & Theories for the Analysis of Event Data 2017 (ATAED 2017), June 26-27, Zaragoza, Spain Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0074-1847-5 UR - http://ceur-ws.org/Vol-1847/ N1 - Satellite event of the conferences: 38th International Conference on Application and Theory of Petri Nets and Concurrency Petri Nets 2017 and 17th International Conference on Application of Concurrency to System Design ACSD 2017, June 26-30, 2017 SP - 139 EP - 157 PB - RWTH CY - Aachen ER - TY - CHAP A1 - Schmitt, Ingo A1 - Römer, Ronald A1 - Wirsching, Günther A1 - Wolff, Matthias T1 - Denormalized Quantum Density Operators for Encoding Semantic Uncertainty in Cognitive Agents T2 - 8th IEEE International Conference on Cognitive Infocommunications CogInfoCom 2017 Proceedings, September 11-14, 2017 Debrecen, Hungary Y1 - 2017 SN - 978-1-5386-1264-4 N1 - IEEE Catalog Number: CFP1726R-ART SP - 165 EP - 170 PB - IEEE CY - Piscataway, NJ ER - TY - VIDEO A1 - Klimczak, Peter A1 - Wirsching, Günther A1 - Wolff, Matthias ED - Barbato, Mariano ED - Löffler, Johannes T1 - Condoms Just Make the Problem Worse: A Formal Semantic Analysis of the AIDS-Discourse Surrounding Pope Benedict N2 - “[…] the scourge [of AIDS] cannot be overcome by the distribution of condoms: on the contrary, they increase it.” The statement above by Pope Benedict XVI, at the beginning of his visit to Africa in March 2009, provoked a strong media reaction. It shall be at the centre of our project to apply a technical method for the analysis of dialogue semantics of spoken utterances, already proven in electronic speech signal processing, to communication between the pope and the press. In doing so, the meaning of an utterance beyond the utterance itself is to be found and affixed to subjective relations to reality, which we call “semantic anchors”. The application of such a method stands to reason in the case of cognitive machines whose 'subjective' realities are fully represented in memory contents; an application to the communication between pope and media appears at first glance less obvious, because it is initially not clear to what extent the media can at all be regarded as a “person” with independent cognitive structures. However, we will show in the following that formal methods can be used successfully even in this context, once the appropriate semantic anchors have been established. In doing so, we can also show that the subjective meanings of the pope's statement cited above are, due to the pope’s and press’s completely different discursive realities and the worlds of thought underlying the utterances, incompatible and thus cannot be squared with each other. KW - media KW - Pope KW - modal logic KW - radical behaviorism KW - cognitive systems Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?rtmp://live.uni-muenster.de/ImperiaVideo/_definst_/imperiavideo/religion_und_moderne/30_popes_on_the_rise___klimczak_wirsching_wolff_.mp4 UR - https://www.uni-muenster.de/Religion-und-Moderne/aktuelles/forschung/videos.html PB - Centrum für Religion und Moderne, Universität Münster CY - Münster ER - TY - GEN A1 - Huber, Markus A1 - Wolff, Matthias A1 - Meyer, Werner A1 - Jokisch, Oliver A1 - Nowack, Kati T1 - Some Design Aspects of a Cognitive User Interface T2 - Online Journal of Applied Knowledge Management N2 - We report on research conducted as part of the Universal Cognitive User Interface (UCUI) project, which aims at developing a universal, autarkic module for intuitive interaction with technical devices. First, we present an empirical study of image schemas as basic building blocks of human knowledge. Image schemas have been studied extensively in cognitive linguistics, but insufficiently in the context of human-computer-interaction (HCI). Some image schemas are developed early at pre-verbal stages (e.g., up-down) and may, thus, exert greater influence on human knowledge than later developed image schemas (e.g., centre-periphery). To investigate this for HCI contexts, we applied a speech interaction task using a Wizard of Oz paradigm. Our results show that users apply early image schemas more frequently than late image schemas. They should, therefore, be given preference in interface designs. In the second part of this contribution we therefore focus on the appropriate representation and processing of semantics. We introduce novel theoretical work including feature-values-relations and Petri net transducers, and discuss their impact on behaviour control of cognitive systems. In addition, we illustrate some details of the implementation regarding learning strategies and the graphical user interface. N2 - ucuikt2015 KW - Cognitive system KW - intuitive interaction KW - image schema theory KW - feature-valuesrelation KW - Petri net transducer and behaviour control Y1 - 2018 UR - http://www.iiakm.org/ojakm/articles/2018/volume6_1.php SN - 2325-4688 N1 - Best Research Paper Award VL - 6 IS - 1 SP - 15 EP - 29 ER - TY - RPRT A1 - Wolff, Matthias T1 - The tikz-3dplot-circleofsphere Package: Drawing circles of a sphere with tikz-3dplot N2 - A circle of a sphere is a circle drawn on a spherical surface like, for instance, circles of latitude or longitude. Circles in arbitrary 3D positions can be drawn with TikZ very easily using a transformed coordinate system provided by the tikz-3dplot package (that is because TikZ can only draw circles on the xy-plane). However, automatically distinguishing the parts of the circle lying on the front and back sides of the sphere, e.g. by drawing a solid arc on the front side and a dashed one on the back side, is a somewhat tricky feat. The tikz-3dplot-circleofsphere package will perform that feat for you. Y1 - 2018 UR - https://www.researchgate.net/publication/326860782_The_tikz-3dplot-circleofsphere_Package_Drawing_circles_of_a_sphere_with_tikz-3dplot U6 - https://doi.org/10.13140/RG.2.2.27314.50888 ER - TY - RPRT A1 - Wolff, Matthias T1 - The tikz-quantumgates Package: Drawing quantum circuits with TikZ N2 - This package provides macros for drawing quantum gates and circuits with TikZ. Y1 - 2018 U6 - https://doi.org/10.13140/RG.2.2.35696.71685 ER - TY - CHAP A1 - Wolff, Matthias A1 - Wirsching, Günther A1 - Huber, Markus A1 - Beim Graben, Peter A1 - Römer, Ronald A1 - Schmitt, Ingo ED - Karpov, Alexey ED - Jokisch, Oliver ED - Potapova, Rodmonga T1 - A Fock Space Toolbox and Some Applications in Computational Cognition T2 - Speech and computer : 20th International Conference, SPECOM 2018, Leipzig, Germany, September 18-22, 2018, proceedings N2 - We present a Matlab toolbox, called “FockBox”, handling Fock spaces and objects associated with Fock spaces: scalars, ket and bra vectors, and linear operators. We give brief application examples from computational linguistics, semantics processing, and quantum logic,demonstrating the use of the toolbox. KW - Fock space KW - Matlab KW - Computational linguistics KW - Semantics processing KW - Cognitive systems KW - Quantum logic KW - Computational cognition Y1 - 2018 SN - 978-3-319-99578-6 U6 - https://doi.org/10.1007/978-3-319-99579-3 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Wolff, Matthias A1 - Huber, Markus A1 - Wirsching, Günther A1 - Römer, Ronald A1 - Beim Graben, Peter A1 - Schmitt, Ingo T1 - Towards a Quantum Mechanical Model of the Inner Stage of Cognitive Agents T2 - 9th IEEE International Conference on Cognitive Infocommunications (CogInfoCom 2018), proceedings, Aug. 22-24, 2018, Budapest, Hungary N2 - We present a model, inspired by quantum field theory, of the so-called inner stage of technical cognitive agents. The inner stage represents all knowledge of the agent. It allows for planning of actions and for higher cognitive functions like coping and fantasy. By the example of a cognitive mouse agent living in a maze wold, we discuss learning, action planning, and attention in a fully deterministic setting and assuming a totally observable world. We explain the relevance of our approach to cognitive infocommunications. KW - cognitive systems KW - cognitive agents KW - quantum field theory KW - machine learning KW - inner stage KW - veridicality KW - attention modeling KW - ontology inference Y1 - 2018 UR - https://ieeexplore.ieee.org/document/8639892 SN - 978-1-5386-7094-1 U6 - https://doi.org/10.1109/CogInfoCom.2018.8639892 N1 - Best Paper Award SP - 147 EP - 152 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Schmitt, Ingo A1 - Wirsching, Günther A1 - Wolff, Matthias ED - Khrennikov, Andrei ED - Melucci, Massimo ED - Bourama, Toni T1 - Quantum-Based Modelling of Database States T2 - Quantum-Like Models for Information Retrieval and Decision-Making Y1 - 2019 UR - https://www.springer.com/de/book/9783030259129 SN - 978-3-030-25912-9 SN - 978-3-030-25913-6 U6 - https://doi.org/10.1007/978-3-030-25913-6 SP - 115 EP - 127 PB - Springer Nature Switzerland AG, Springer International Publishing CY - Cham ET - 1. Auflage ER - TY - GEN A1 - Römer, Ronald A1 - beim Graben, Peter A1 - Huber, Markus A1 - Wolff, Matthias A1 - Wirsching, Günther A1 - Schmitt, Ingo T1 - Behavioral Control of Cognitive Agents Using Database Semantics and Minimalist Grammars T2 - Proceedings 10th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2019, Oct. 23-25 Y1 - 2019 SN - 978-1-7281-4793-2 SN - 978-1-7281-4792-5 U6 - https://doi.org/10.1109/CogInfoCom47531.2019.9089947 SN - 2380-7350 SP - 73 EP - 78 CY - Naples, Italy ER - TY - GEN A1 - Beim Graben, Peter A1 - Römer, Ronald A1 - Meyer, Werner A1 - Huber, Markus A1 - Wolff, Matthias T1 - Reinforcement learning of minimalist numeral grammars T2 - 10th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), Naples, Italy N2 - Speech-controlled user interfaces facilitate the operation of devices and household functions to laymen. State-of-the-art language technology scans the acoustically analyzed speech signal for relevant keywords that are subsequently inserted into semantic slots to interpret the user's intent. In order to develop proper cognitive information and communication technologies, simple slot-filling should be replaced by utterance meaning transducers (UMT) that are based on semantic parsers and a mental lexicon, comprising syntactic, phonetic and semantic features of the language under consideration. This lexicon must be acquired by a cognitive agent during interaction with its users. We outline a reinforcement learning algorithm for the acquisition of the syntactic morphology and arithmetic semantics of English numerals, based on minimalist grammar (MG), a recent computational implementation of generative linguistics. Number words are presented to the agent by a teacher in form of utterance meaning pairs (UMP) where the meanings are encoded as arithmetic terms. Since MG encodes 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. Y1 - 2019 UR - https://arxiv.org/abs/1906.04447 SN - 978-1-7281-4793-2 SN - 978-1-7281-4792-5 SN - 978-1-7281-4794-9 U6 - https://doi.org/10.1109/CogInfoCom47531.2019.9089924 SN - 2380-7350 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 - 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 - 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 - 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 - Tschöpe, Constanze A1 - Hentschel, Dieter A1 - Wolff, Matthias A1 - Eichner, Matthias A1 - Hoffmann, Rüdiger T1 - Classification of non-speech acoustic signals using structure models T2 - Proceedings, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 17 - 21, 2004, Montreal, Canada, vol. 5 N2 - Non-speech acoustic signals are widely used as the input of systems for non-destructive testing. In this rapidly growing field, the signals have an increasing complexity leading to the fact that powerful models are required. Methods like DTW and HMM, which are established in speech recognition, have been successfully used but are not sufficient in all cases. We propose the application of generalized structured Markov graphs (SMG). We describe a task independent structure learning technique which automatically adapts the models to the structure of the test signals. We demonstrate that our solution outperforms hand-tuned HMM structures in terms of class discrimination by two case studies using data from real applications. Y1 - 2004 SN - 0-7803-8484-9 U6 - https://doi.org/10.1109/ICASSP.2004.1327195 VL - 5 SP - 653 EP - 656 PB - IEEE Operations Center CY - Piscataway, NJ 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 - 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 - 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 - 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 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 - 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 - 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 - 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 - CHAP A1 - Kraljevski, Ivan A1 - Tschöpe, Constanze A1 - Wolff, Matthias ED - Klimczak, Peter ED - Petersen, Christer T1 - Limits and Prospects of Big Data and Small Data Approaches in AI Applications T2 - AI - Limits and Prospects of Artificial Intelligence N2 - The renaissance of artificial intelligence (AI) in the last decade can be credited to several factors, but chief among these is the ever-increasing availability and miniaturization of computational resources. This process has contributed to the rise of ubiquitous computing via popularizing smart devices and the Internet of Things in everyday life. In turn, this has resulted in the generation of increasingly enormous amounts of data. The tech giants are harvesting and storing data on their clients’ behavior and, at the same time, introducing concerns about data privacy and protection. Suddenly, such an abundance of data and computing power, which was unimaginable a few decades ago, has caused a revival of old and the invention of new machine learning paradigms, like Deep Learning. Artificial intelligence has undergone a technological breakthrough in various fields, achieving better than human performance in many areas (such as vision, board games etc.). More complex tasks require more sophisticated algorithms that need more and more data. It has often been said that data is becoming a resource that is "more valuable than oil"; however, not all data is equally available and obtainable. Big data can be described by using the "four Vs"; data with immense velocity, volume, variety, and low veracity. In contrast, small data do not possess any of those qualities; they are limited in size and nature and are observed or produced in a controlled manner. Big data, along with powerful computing and storage resources, allow “black box” AI algorithms for various problems previously deemed unsolvable. One could create AI applications even without the underlying expert knowledge, assuming there are enough data and the right tools available (e.g. end-to-end speech recognition and generation, image and object recognition). There are numerous fields in science, industry and everyday life where AI has vast potential. However, due to the lack of big data, application is not straightforward or even possible. A good example is AI in medicine, where an AI system is intended to assist physicians in diagnosing and treating rare or previously never observed conditions, and there is no or an insufficient amount of data for reliable AI deployment. Both big and small data concepts have limitations and prospects for different fields of application. This paper will try to identify and present them by giving real-world examples in various AI fields. Y1 - 2023 UR - https://www.transcript-verlag.de/chunk_detail_seite.php?doi=10.14361%2F9783839457320-006 SN - 978-3-8376-5732-6 U6 - https://doi.org/10.14361/9783839457320-006 SP - 115 EP - 142 PB - transcript Verlag CY - Bielefeld ER - TY - GEN A1 - Uhlig, Sebastian A1 - Alkhasli, Ilkin A1 - Schubert, Frank A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - A Review of Synthetic and Augmented Training Data for Machine Learning in Ultrasonic Non-Destructive Evaluation T2 - Ultrasonics N2 - Ultrasonic Testing (UT) has seen increasing application of machine learning (ML) in recent years, promoting higher-level automation and decision-making in flaw detection and classification. Building a generalized training dataset to apply ML in non-destructive evaluation (NDE), and thus UT, is exceptionally difficult since data on pristine and representative flawed specimens are needed. Yet, in most UT test cases flawed specimen data is inherently rare making data coverage the leading problem when applying ML. Common data augmentation (DA) strategies offer limited solutions as they don’t increase the dataset variance, which can lead to overfitting of the training data. The virtual defect method and the recent application of generative adversarial neural networks (GANs) in UT are sophisticated DA methods targeting to solve this problem. On the other hand, well-established research in modeling ultrasonic wave propagations allows for the generation of synthetic UT training data. In this context, we present a first thematic review to summarize the progress of the last decades on synthetic and augmented UT training data in NDE. Additionally, an overview of methods for synthetic UT data generation and augmentation is presented. Among numerical methods such as finite element, finite difference, and elastodynamic finite integration methods, semi-analytical methods such as general point source synthesis, superposition of Gaussian beams, and the pencil method as well as other UT modeling software are presented and discussed. Likewise, existing DA methods for one- and multidimensional UT data, feature space augmentation, and GANs for augmentation are presented and discussed. The paper closes with an in-detail discussion of the advantages and limitations of existing methods for both synthetic UT training data generation and DA of UT data to aid the decision-making of the reader for the application to specific test cases. KW - Non-destructive testing KW - NDT KW - Non-destructive evaluation KW - NDE KW - Ultrasonic testing KW - Ultrasonics KW - Flaw detection KW - Machine learning KW - Artificial intelligence KW - Deep learning KW - Synthetic training data KW - Data augmentation Y1 - 2023 UR - https://www.sciencedirect.com/science/article/pii/S0041624X23001178 U6 - https://doi.org/10.1016/j.ultras.2023.107041 SN - 1874-9968 IS - 134 ER - TY - GEN A1 - Maier, Isidor Konrad A1 - Kuhn, Johannes Ferdinand Joachim A1 - Duckhorn, Frank A1 - Kraljevski, Ivan A1 - Sobe, Daniel A1 - Wolff, Matthias A1 - Tschöpe, Constanze T1 - Word Class Based Language Modeling: A Case of Upper Sorbian T2 - Proceedings of The Workshop on Resources and Technologies for Indigenous, Endangered and Lesser-resourced Languages in Eurasia within the 13th Language Resources and Evaluation Conference, Marseille, France N2 - In this paper we show how word class based language modeling can support the integration of a small language in modern applications of speech technology. The methods described in this paper can be applied for any language. We demonstrate the methods on Upper Sorbian. The word classes model the semantic expressions of numerals, date and time of day. The implementation of the created grammars was realized in the form of finite-state-transducers (FSTs) and minimalists grammars (MGs). We practically demonstrate the usage of the FSTs in a simple smart-home speech application, that is able to set wake-up alarms and appointments expressed in a variety of spontaneous and natural sentences. While the created MGs are not integrated in an application for practical use yet, they provide evidence that MGs could potentially work more efficient than FSTs in built-on applications. In particular, MGs can work with a significantly smaller lexicon size, since their more complex structure lets them generate more expressions with less items, while still avoiding wrong expressions. KW - word classes, minimalist grammar, language modeling, speech recognition, Upper Sorbian Y1 - 2022 UR - http://www.lrec-conf.org/proceedings/lrec2022/workshops/EURALI/pdf/2022.eurali-1.5.pdf SN - 978-2-493814-07-4 SP - 28 EP - 35 PB - European Language Resources Association ER - TY - GEN A1 - Kraljevski, Ivan A1 - Ju, Yong Chul A1 - Ivanov, Dmitrij A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - How to Do Machine Learning with Small Data? - A Review from an Industrial Perspective T2 - arXiv N2 - Artificial intelligence experienced a technological breakthrough in science, industry, and everyday life in the recent few decades. The advancements can be credited to the ever-increasing availability and miniaturization of computational resources that resulted in exponential data growth. However, because of the insufficient amount of data in some cases, employing machine learning in solving complex tasks is not straightforward or even possible. As a result, machine learning with small data experiences rising importance in data science and application in several fields. The authors focus on interpreting the general term of "small data" and their engineering and industrial application role. They give a brief overview of the most important industrial applications of machine learning and small data. Small data is defined in terms of various characteristics compared to big data, and a machine learning formalism was introduced. Five critical challenges of machine learning with small data in industrial applications are presented: unlabeled data, imbalanced data, missing data, insufficient data, and rare events. Based on those definitions, an overview of the considerations in domain representation and data acquisition is given along with a taxonomy of machine learning approaches in the context of small data. Y1 - 2023 UR - https://arxiv.org/abs/2311.07126 ER - TY - GEN A1 - Kraljevski, Ivan A1 - Duckhorn, Frank A1 - Tschöpe, Constanze A1 - Schubert, Frank A1 - Wolff, Matthias T1 - Paper Tissue Softness Rating by Acoustic Emission Analysis T2 - Applied Sciences N2 - 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. KW - acoustic emission KW - machine learning KW - tissue softness analysis Y1 - 2022 U6 - https://doi.org/10.3390/app13031670 SN - 2076-3417 VL - 13 IS - 3 ER - TY - GEN A1 - Ju, Yong Chul A1 - Kraljevski, Ivan A1 - Neunübel, Heiko A1 - Tschöpe, Constanze A1 - Wolff, Matthias T1 - Acoustic Resonance Testing of Small Data on Sintered Cogwheels T2 - Sensors N2 - Based on the fact that cogwheels are indispensable parts in manufacturing, we present the acoustic resonance testing (ART) of small data on sintered cogwheels for quality control in the context of non-destructive testing (NDT). Considering the lack of extensive studies on cogwheel data by means of ART in combination with machine learning (ML), we utilize time-frequency domain feature analysis and apply ML algorithms to the obtained feature sets in order to detect damaged samples in two ways: one-class and binary classification. In each case, despite small data, our approach delivers robust performance: All damaged test samples reflecting real-world scenarios are recognized in two one-class classifiers (also called detectors), and one intact test sample is misclassified in binary ones. This shows the usefulness of ML and time-frequency domain feature analysis in ART on a sintered cogwheel dataset. KW - acoustic resonance testing (ART) non-destructive testing (NDT) KW - deep learning KW - machine learning KW - small-data KW - non-destructive testing (NDT) Y1 - 2022 U6 - https://doi.org/10.3390/s22155814 SN - 1424-8220 VL - 22 IS - 15 ER - TY - GEN A1 - Maier, Isidor Konrad A1 - Kuhn, Johannes A1 - Duckhorn, Frank A1 - Kraljevski, Ivan A1 - Sobe, Daniel A1 - Wolff, Matthias A1 - Tschöpe, Constanze T1 - Word Class Based Language Modeling: A Case of Upper Sorbian, LREC 2022, Marseille T2 - Language Resources and Evaluation Conference 2022 (LREC 2022), Marseille, 2022-06-13 Y1 - 2022 U6 - https://doi.org/10.5281/zenodo.7501145 ER - TY - GEN A1 - Römer, Ronald A1 - Huber-Liebl, Markus A1 - Wolff, Matthias T1 - Quantum-inspired representation and querying of semiotic object properties by cognitive agents T2 - 2025 IEEE 16th International Conference on Cognitive Infocommunications (CogInfoCom) N2 - Advanced intelligence often relies on the ability to build and use models. They allow the representation of knowledge, enable predictions, and serve to plan goal-directed actions. However, the successfull use of models requires a certain level of competence in interacting with models. This competence can be acquired by exploiting the separation of the cognitive agent from the objects represented in the model; because it allows the differentiation of individual semiotic levels. This includes the separation of self-sufficient and non self-sufficient object attributes. Non self-sufficient attributes that the agent assigned to potential target objects during the exploration phase form the starting point for the information requirement regarding the self-sufficient attributes of these objects. These attributes are required for target selection and the subsequent alignment of the model-based planning. This process is characterized by a series of queries to the environment model and thus shows a certain similarity to information retrieval (IR). Therefore, in this work we particularly investigate quantum-inspired IR-methods for representation and querying. We demonstrate that they are suitable for modelling cognitive effort and behavior, as they represent a realistic and universally applicable descriptive tool. KW - Information retrieval KW - Semiotics KW - Planning Y1 - 2025 SN - 979-8-3503-5691-5 U6 - https://doi.org/10.1109/CogInfoCom66819.2025.11200567 SP - 000129 EP - 000134 PB - IEEE CY - Piscataway, NJ ER - TY - GEN A1 - Huber-Liebl, Markus A1 - Rosenow, Tillmann A1 - Römer, Ronald A1 - Wirsching, Günther A1 - Wolff, Matthias T1 - Knowledge representation and querying with tensors for a class of practical test problems T2 - Refereed Paper Proceedings - KM Conference 2025 – Siena, Italy 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 and querying. We discuss ideas from information retrieval and translate them into our method of behavioral control. We formalize the method with tensor algebra and discuss its extensions to learning. At the example of the problem of 𝑁-dimensional aiming, we visualize the transfer of our stated theoretical foundation to a class of practical test problems. KW - Knowledge representation KW - Cognitive agents KW - Tensor algebra KW - Quantum inspiration Y1 - 2025 UR - https://www.iiakm.org/conference/proceedings/KM2025_RefereedProceedingsPapers.pdf SP - 111 EP - 123 PB - International Institute for Applied Knowledge Management ER - TY - GEN A1 - Schmitt, Ingo A1 - Sowoidnich, Kay A1 - Gosswami, Tapashi A1 - Sumpf, Bernd A1 - Maiwald, Martin A1 - Wolff, Matthias T1 - PCA-based peak feature selection for classification of spectroscopic datasets T2 - Journal of chemometrics N2 - Reducing feature dimensionality in spectroscopic data is crucial for efficient analysis and classification. Using all available features for classification typically results in an unacceptably high runtime and poor accuracy. Popular feature extraction methods, such as principal component analysis (PCA), linear discriminant analysis (LDA), and autoencoders, reduce feature dimensionality by extracting latent features that can be challenging to interpret. To enable better human interpretation of the classification model, we avoid extraction methods and instead propose applying feature selection methods. In this work, we develop an innovative PCA-based feature selection method for spectroscopic data, providing an essential subset of the original features. As an important advantage, no prior knowledge about the characteristic signals of the respective target substance is required. In this proof-of-concept study, the proposed method is initially characterized using simulated Raman and infrared absorption datasets. From the top five PCA eigenvectors of spectroscopic data, we identify a set of three top peaks each at specific wavenumbers (features). The compact set of selected features is then used for classification tasks applying a decision tree. Based on two well-defined spectroscopic datasets, our study demonstrates that our new method of PCA-based peak finding outperforms selected other approaches with regard to interpretability and accuracy. For both investigated datasets, accuracies greater than 97% are achieved. Our approach shows large potential for accurate classification combined with interpretability in further scenarios involving spectroscopic datasets. KW - Cclassification KW - Decision tree KW - Peak finding KW - Principal component analysis KW - Spectroscopic data Y1 - 2025 U6 - https://doi.org/10.1002/cem.70074 SN - 0886-9383 SN - 1099-128X VL - 39 IS - 11 SP - 1 EP - 14 PB - John Wiley & Sons Ltd. CY - New York, NY ER -