November 2022 - informatik-vortraege

Einladung Informatik Oberseminar Christian Cherek
by Cherek, Christian 21 Nov '22

21 Nov '22

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Montag, 28. November 2022, 14:30 Uhr Ort: Raum 2222, Ahornstr. 55 Referent: Christian Cherek M.Sc. Lehrstuhl Informatik 10 Thema: The Impact of Tangible Interaction Techniques on Higher Cognitive Processes Abstract: Multitouch interaction brought incredible advancements to our everyday life. The success of smartphones is unprecedented in modern history for a good reason. On multitouch displays, input and output are collocated at the tip of our fingers. This enables immediate feedback, highly flexible utilization of the available space, updatability of interfaces, and new accessibility features. However, a touchscreen's flat surface lacks haptic features, neglecting a big part of our sensory capabilities. This thesis integrates itself into the tangible research community by presenting novel ways to create tangibles for capacitive screens and presenting a software framework to develop tangible applications with Apple's native APIs. We developed the Design Space of Tangible Interaction, a taxonomy to help researchers and designers comparing tangible designs and finding new ways to interact with tangibles. In this spirit, we evaluated tangibles in novel ways beyond their well-established usability benefits. We found them to contribute to users' way of thinking, awareness for collaborators, and intuitiveness of highly complex input tasks. Es laden ein: die Dozentinnen und Dozenten der Informatik

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Einladung Informatik-Oberseminar Parnia Bahar, 24. November 2022,
by Stephanie Jansen 16 Nov '22

16 Nov '22

********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * *********************************************************************** Zeit: Donnerstag, 24. November 2022, 10:00 Uhr Zoom: https://rwth.zoom.us/j/93616983610?pwd=UnkwdWd4azRSNzVVUEt4WW1FdHNJUT09 Meeting-ID: 936 1698 3610 Kenncode: 382088 Referentin: Parnia Bahar, M.Sc. Thema: Neural Sequence-to-Sequence Modeling for Language and Speech Translation Abstract: In recent years, various fields in human language technology have been advanced by the success of neural sequence-to-sequence modeling. The application of attention models to automatic speech recognition, text, and speech machine translation has become dominant and well-established. Although the effectiveness of such models has been documented in scientific papers, not all aspects of attention sequence-to-sequence models have been explored. Therefore, the main contribution of this thesis centers around redesigning attention models by proposing novel alternative architectures. From a modeling perspective, this research goes beyond current sequence-to-sequence backbone models to directly incorporate input and output sequences in a two-dimensional structure where an attention mechanism is no longer required. This model distinguishes itself from attention models in which inputs and outputs are treated as one-dimensional sequences over time. Current state-of-the-art attention models also lack an explicit alignment, a core component of traditional systems. Such a gross simplification of a complex process complicates the extraction of alignments between input and output positions. To enable the explainability of attention models and more controllable output, the next part of this study integrates the attention model into the hidden Markov model formulation by introducing alignments as a sequence of hidden variables. Finally, an exciting research direction is combining speech recognition with text machine translation for speech-to-text translation. Besides advancing a cascade of independently trained speech recognition and machine translation systems, this thesis sheds light on different end-to-end models to directly translate speech into a target text and shows that such end-to-end models can practically translate speech utterances as a substitute solution to cascaded speech translation. Es laden ein: die Dozentinnen und Dozenten der Informatik -- Stephanie Jansen Faculty of Mathematics, Computer Science and Natural Sciences HLTPR - Human Language Technology and Pattern Recognition RWTH Aachen University Theaterstraße 35-39 D-52062 Aachen Tel: +49 241 80-21601 sek(a)hltpr.rwth-aachen.de www.hltpr.rwth-aachen.de

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Einladung: Informatik-Oberseminar Herr Daxin Liu
by Maaßen, Leany 09 Nov '22

09 Nov '22

+********************************************************************** * * * Einladung * * * * Informatik-Oberseminar * * * +********************************************************************** Zeit: Montag, 21.11.2022, 14:00-15:00 Uhr Der öffentliche Vortrag findet hybrid statt: Raum: Raum 5053.2 (B-IT-Hörsaal)/Informatikzentrum, Ahornstraße 55 Zoom: https://rwth.zoom.us/j/96565981989?pwd=b3B3aEVmSnJ1VFJhUDYwSlorbTcvQT09 Meeting-ID: 965 6598 1989 Kenncode: 346594 Referent: Herr Daxin Liu, M. Sc. LuFG Informatik 5 Thema: Projection in a Probabilistic Epistemic Logic and Its Application to Belief-based-Program Verification Abstract: Rich representation of knowledge and actions has been a goal that many AI researchers pursue. Among all proposals, perhaps, the situation calculus by Reiter is the most widely studied, where actions are treated as logical terms and the agent's knowledge is represented by logical formulas. The language has been extended to incorporate many features like time, concurrency, procedures, etc.. Most recently, Belle and Lakemeyer proposed a modal logic DS which deals with degrees of belief and noisy sensing. The logic has many appealing properties like full introspection, however, it also has some shortcomings. Perhaps the main one is the lack of expressiveness when it comes to degrees of belief. Currently, the language allows expressing degrees of belief only as constants making it impossible to express belief distribution. Another important problem is that it lacks projection reasoning mechanisms. Projection is the task to determine whether a query about the future is entailed by an initial knowledge base. Two solutions of projection exist regression and progression. While regression transfers the query about the future into a query about the initial state and evaluates it there, progression transfers the whole initial knowledge base into a future one. In this thesis, we first lift the expressiveness of the logic DS by modifying both the syntax and semantics. Moreover, we investigate the projection problem in DS. In particular, we propose a regression operator which can handle queries with nested beliefs and beliefs with quantifying-in. For progression, we show that classical progression is first-order definable for a fragment of the logic and provide our solution for the progression of belief in terms of only-believing after actions. Moreover, we exploit how to apply the proposed methods in a more practical scenario: on the verification of belief programs, a probabilistic extension of Golog programs, where every action and sensing could be noisy and every test refers to the agent's subjective beliefs. We show that the verification problem is undecidable even in very restrictive settings. We also show a special case where the problem is decidable. Es laden ein: die Dozentinnen und Dozenten der Informatik _______________________________ Leany Maaßen RWTH Aachen University Lehrstuhl Informatik 5, LuFG Informatik 5 Prof. Dr. Stefan Decker, Prof. Dr. Matthias Jarke, Prof. Gerhard Lakemeyer Ph.D., JunProf. Dr. Sandra Geisler Ahornstrasse 55 D-52074 Aachen Tel: 0241-80-21509 Fax: 0241-80-22321 E-Mail: maassen(a)dbis.rwth-aachen.de

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