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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6...38 Hits 21 – 40 of 760 21 Using Spoken Dialogue Technology for L2 Speaking Practice: What Do Teachers Think? Timpe-Laughlin, Veronika; Sydorenko, Tetyana; Daurio, Phoebe In: Applied Linguistics Faculty Publications and Presentations (2020) BASE Show details 22 Towards Programming in Natural Language: Learning New Functions from Spoken Utterances ... Weigelt, Sebastian; Steurer, Vanessa; Hey, Tobias. - : World Scientific Publishing, 2020 BASE Show details 23 Designing Internet of Tangible Things for Children with Hearing Impairment Cano; Peñeñory; Collazos... In: Information ; Volume 11 ; Issue 2 (2020) BASE Show details 24 User Experience of Alexa when controlling music - comparison of face and construct validity of four questionnaires Brüggemeier, Birgit; Breiter, Michael; Kurz, Miriam... In: Fraunhofer IIS (2020) BASE Show details 25 Comparison of Machine Learning Models: Gesture Recognition Using a Multimodal Wrist Orthosis for Tetraplegics Martin, Charlie In: The Journal of Purdue Undergraduate Research (2020) BASE Show details 26 Towards Programming in Natural Language: Learning New Functions from Spoken Utterances Hey, Tobias; Weigelt, Sebastian; Steurer, Vanessa; Tichy, Walter F. In: International journal of semantic computing, 14 (2), 249–272 ; ISSN: 1793-351X, 1793-7108 (2020) Abstract: Systems with conversational interfaces are rather popular nowadays. However, their full potential is not yet exploited. For the time being, users are restricted to calling predefined functions. Soon, users will expect to customize systems to their needs and create own functions using nothing but spoken instructions. Thus, future systems must understand how laypersons teach new functionality to intelligent systems. The understanding of natural language teaching sequences is a first step toward comprehensive end-user programming in natural language. We propose to analyze the semantics of spoken teaching sequences with a hierarchical classification approach. First, we classify whether an utterance constitutes an effort to teach a new function or not. Afterward, a second classifier locates the distinct semantic parts of teaching efforts: declaration of a new function, specification of intermediate steps, and superfluous information. For both tasks we implement a broad range of machine learning techniques: classical approaches, such as Naïve Bayes, and neural network configurations of various types and architectures, such as bidirectional LSTMs. Additionally, we introduce two heuristic-based adaptations that are tailored to the task of understanding teaching sequences. As data basis we use 3168 descriptions gathered in a user study. For the first task convolutional neural networks obtain the best results (accuracy: 96.6%); bidirectional LSTMs excel in the second (accuracy: 98.8%). The adaptations improve the first-level classification considerably (plus 2.2% points). Keyword: artificial intelligence; computational linguistics; conversational interfaces; DATA processing & computer science; ddc:004; end-user programming; info:eu-repo/classification/ddc/004; intelligent systems; machine learning; natural language processing; natural language understanding; naturalistic programming; neural networks; Programming in natural language; spoken language understanding URL: https://publikationen.bibliothek.kit.edu/1000124405 https://doi.org/10.5445/IR/1000124405/post https://publikationen.bibliothek.kit.edu/1000124405/130160664 BASE Hide details 27 Interfaces móveis para o sistema Nuada em contexto fisioterapêutico Moura, João Pedro Soares de. - 2020 BASE Show details 28 Intelligente Persönliche Assistenten im häuslichen Umfeld : Erkenntnisse aus einer linguistischen Pilotstudie zur Erhebung audiovisueller Interaktionsdaten Hector, Tim Moritz; Hrncal, Christine. - : Universität Siegen, 2020. : DFG-Sonderforschungsbereich 1187 "Medien der Kooperation", 2020 In: SFB 1187 Medien der Kooperation: Working Paper Series, No. 14, 2020. - URL: https://www001.zimt.uni-siegen.de/ojs/index.php/wps1187/issue/view/19. - ISSN: 2567-2517 (2020) BASE Show details 29 Usage-Based Learning in Human Interaction with an Adaptive Virtual Assistant Delgrange, Clément; Dussoux, Jean-Michel; Dominey, Peter In: ISSN: 2379-8920 ; EISSN: 2379-8939 ; IEEE Transactions on Cognitive and Developmental Systems ; https://hal.archives-ouvertes.fr/hal-02414815 ; IEEE Transactions on Cognitive and Developmental Systems, Institute of Electrical and Electronics Engineers, Inc, 2019 (2019) BASE Show details 30 Free Ocean CO2 Enrichment (FOCE) experiments: Scientific and technical recommendations for future in situ ocean acidification projects Stark, Jonathan; Peltzer, Edward; Kline, David... In: ISSN: 0079-6611 ; Progress in Oceanography ; https://hal.archives-ouvertes.fr/hal-02332356 ; Progress in Oceanography, Elsevier, 2019, 172, pp.89-107. ⟨10.1016/j.pocean.2019.01.006⟩ (2019) BASE Show details 31 Experiencing the Presence: Degrees of Closeness in the Digital Biographies of Migration ... Dusi, Nicola; Razzoli, Damiano. - : Cinergie – Il Cinema e le altre Arti, 2019 BASE Show details 32 ImAc: Enabling Immersive, Accessible and Personalized Media Experiences ... Montagud, Mario; Fraile, Isaac; Nuñez, Juan A.. - : Zenodo, 2019 BASE Show details 33 ImAc: Enabling Immersive, Accessible and Personalized Media Experiences ... Montagud, Mario; Fraile, Isaac; Nuñez, Juan A.. - : Zenodo, 2019 BASE Show details 34 An Effective and Efficient Genetic-Fuzzy Algorithm for Supporting Advanced Human-Machine Interfaces in Big Data Settings Alfredo Cuzzocrea; Giorgio Mario Grasso; Enzo Mumolo In: Algorithms ; Volume 13 ; Issue 1 (2019) BASE Show details 35 Can gapping be embedded? Experimental evidence from Spanish Bîlbîie, Gabriela; de la Fuente, Israel In: Glossa: a journal of general linguistics; Vol 4, No 1 (2019); 110 ; 2397-1835 (2019) BASE Show details 36 Fourteen-channel EEG with Imagined Speech (FEIS) dataset ... Wellington, Scott; Clayton, Jonathan. - : Zenodo, 2019 BASE Show details 37 Fourteen-channel EEG with Imagined Speech (FEIS) dataset ... Wellington, Scott; Clayton, Jonathan. - : Zenodo, 2019 BASE Show details 38 Puppet Dubbing ... Fried, Ohad; Agrawala, Maneesh. - : The Eurographics Association, 2019 BASE Show details 39 De-syntacticising Syntax? : Concerns on the Architecture of Grammar and the Role of Interface Components Irurtzun, Aritz. - 2019 BASE Show details 40 Generative Grammar and the Faculty of Language : Insights, Questions, and Challenges Chomsky, Noam; Gallego, Ángel J.; Ott, Dennis. - 2019 BASE Show details Page: 1 2 3 4 5 6...38

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