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Fast Classification Learning with Neural Networks and Conceptors for Speech Recognition and Car Driving Maneuvers

Title data

Krause, Stefanie ; Otto, Oliver ; Stolzenburg, Frieder:
Fast Classification Learning with Neural Networks and Conceptors for Speech Recognition and Car Driving Maneuvers.
In: Multi-disciplinary Trends in Artificial Intelligence : 14th International Conference, MIWAI 2021, Virtual Event, July 2–3, 2021 ; Proceedings. - Cham : Springer , 2021 . - pp. 45-57
ISBN 978-3-030-80253-0
DOI: https://doi.org/10.1007/978-3-030-80253-0_5

Official URL: Volltext

Abstract in another language

Recurrent neural networks are a powerful means in diverse applications. We show that, together with so-called conceptors, they also allow fast learning, in contrast to other deep learning methods. In addition, a relatively small number of examples suffices to train neural networks with high accuracy. We demonstrate this with two applications, namely speech recognition and detecting car driving maneuvers. We improve the state of the art by application-specific preparation techniques: For speech recognition, we use mel frequency cepstral coefficients leading to a compact representation of the frequency spectra and detecting car driving maneuvers can be done without the commonly used polynomial interpolation, as our evaluation suggests.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Recurrent neural networks; Classification with conceptors; Fast learning; Speech recognition; Detecting car driving maneuvers
Institutions of the University: Faculties
Faculties > Faculty of Law, Business and Economics
Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration XVII - Information Systems and Value-Based Business Process Management
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration XVII - Information Systems and Value-Based Business Process Management > Chair Information Systems and Value-Based Business Process Management - Univ.-Prof. Dr. Maximilian Röglinger
Research Institutions
Research Institutions > Research Centres > Forschungszentrum für Modellbildung und Simulation (MODUS)
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering
Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 02 Jul 2021 10:10
Last Modified: 07 Sep 2021 12:16
URI: https://eref.uni-bayreuth.de/id/eprint/66400