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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 Hits 1 – 20 of 30 1 Grounding Hindsight Instructions in Multi-Goal Reinforcement Learning for Robotics ... Röder, Frank; Eppe, Manfred; Wermter, Stefan. - : arXiv, 2022 BASE Show details 2 LipSound2: Self-Supervised Pre-Training for Lip-to-Speech Reconstruction and Lip Reading ... Qu, Leyuan; Weber, Cornelius; Wermter, Stefan. - : arXiv, 2021 BASE Show details 3 Neural Network Learning for Robust Speech Recognition Qu, Leyuan. - : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2021 BASE Show details 4 Towards a self-organizing pre-symbolic neural model representing sensorimotor primitives ... Zhong, Junpei; Cangelosi, Angelo; Wermter, Stefan. - : arXiv, 2020 BASE Show details 5 Conversational Language Learning for Human-Robot Interaction Bothe, Chandrakant Ramesh. - : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2020 BASE Show details 6 Crossmodal Language Grounding in an Embodied Neurocognitive Model Heinrich, Stefan; Yao, Yuan; Hinz, Tobias... In: Front Neurorobot (2020) BASE Show details 7 Incorporating End-to-End Speech Recognition Models for Sentiment Analysis ... Lakomkin, Egor; Zamani, Mohammad Ali; Weber, Cornelius. - : arXiv, 2019 BASE Show details 8 Towards Dialogue-based Navigation with Multivariate Adaptation driven by Intention and Politeness for Social Robots ... Bothe, Chandrakant; Garcia, Fernando; Maya, Arturo Cruz. - : arXiv, 2018 BASE Show details 9 GradAscent at EmoInt-2017: Character- and Word-Level Recurrent Neural Network Models for Tweet Emotion Intensity Detection ... Lakomkin, Egor; Bothe, Chandrakant; Wermter, Stefan. - : arXiv, 2018 BASE Show details 10 Syntactic Reanalysis in Language Models for Speech Recognition Twiefel, Johannes; Hinaut, Xavier; Wermter, Stefan In: 2017 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) ; https://hal.inria.fr/hal-01558462 ; 2017 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), Sep 2017, Lisbon, Portugal ; http://icdl-epirob.org/ (2017) BASE Show details 11 Interactive Natural Language Acquisition in a Multi-modal Recurrent Neural Architecture ... Heinrich, Stefan; Wermter, Stefan. - : arXiv, 2017 BASE Show details 12 Recurrent Neural Network for Syntax Learning with Flexible Predicates for Robotic Architectures Hinaut, Xavier; Twiefel, Johannes; Wermter, Stefan In: The Sixth Joint IEEE International Conference Developmental Learning and Epigenetic Robotics (ICDL-EPIROB) ; https://hal.inria.fr/hal-01417697 ; The Sixth Joint IEEE International Conference Developmental Learning and Epigenetic Robotics (ICDL-EPIROB), Sep 2016, Cergy, France ; http://icdl-epirob.org/ (2016) BASE Show details 13 Semantic Role Labelling for Robot Instructions using Echo State Networks Twiefel, Johannes; Hinaut, Xavier; Wermter, Stefan In: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) ; https://hal.inria.fr/hal-01417701 ; European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Apr 2016, Bruges, Belgium ; https://www.elen.ucl.ac.be/esann/index.php?pg=esann16_programme (2016) BASE Show details 14 Using Natural Language Feedback in a Neuro-inspired Integrated Multimodal Robotic Architecture Twiefel, Johannes; Hinaut, Xavier; Borghetti, Marcelo... In: 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN) ; https://hal.inria.fr/hal-01417706 ; 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), Aug 2016, New York City, United States. pp.52 - 57, ⟨10.1109/ROMAN.2016.7745090⟩ ; http://www.tc.columbia.edu/conferences/roman2016/ (2016) BASE Show details 15 Natural language acquisition in recurrent neural architectures ; Erwerb von natürlicher Sprache in rekurrenten neuronalen Architekturen Heinrich, Stefan. - : Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky, 2016 BASE Show details 16 A Recurrent Neural Network for Multiple Language Acquisition: Starting with English and French Hinaut, Xavier; Twiefel, Johannes; Petit, Maxime... In: Proceedings of the NIPS Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches (CoCo 2015) ; https://hal.inria.fr/hal-02561258 ; Proceedings of the NIPS Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches (CoCo 2015), Dec 2015, Montreal, Canada ; http://ceur-ws.org/Vol-1583/ (2015) BASE Show details 17 Toward a self-organizing pre-symbolic neural model representing sensorimotor primitives Zhong, Junpei; Cangelosi, Angelo; Wermter, Stefan. - 2014 BASE Show details 18 Toward a self-organizing pre-symbolic neural model representing sensorimotor primitives Zhong, Junpei; Cangelosi, Angelo; Wermter, Stefan. - : Frontiers Media S.A., 2014 Abstract: The acquisition of symbolic and linguistic representations of sensorimotor behavior is a cognitive process performed by an agent when it is executing and/or observing own and others' actions. According to Piaget's theory of cognitive development, these representations develop during the sensorimotor stage and the pre-operational stage. We propose a model that relates the conceptualization of the higher-level information from visual stimuli to the development of ventral/dorsal visual streams. This model employs neural network architecture incorporating a predictive sensory module based on an RNNPB (Recurrent Neural Network with Parametric Biases) and a horizontal product model. We exemplify this model through a robot passively observing an object to learn its features and movements. During the learning process of observing sensorimotor primitives, i.e., observing a set of trajectories of arm movements and its oriented object features, the pre-symbolic representation is self-organized in the parametric units. These representational units act as bifurcation parameters, guiding the robot to recognize and predict various learned sensorimotor primitives. The pre-symbolic representation also accounts for the learning of sensorimotor primitives in a latent learning context. Keyword: Neuroscience URL: https://doi.org/10.3389/fnbeh.2014.00022 http://www.ncbi.nlm.nih.gov/pubmed/24550798 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3912404 BASE Hide details 19 Temporal sequence detection with spiking neurons: towards recognizing robot language instructions Panchev, Christo; Wermter, Stefan In: Connection science. - Abingdon, Oxfordshire : Taylor & Francis 18 (2006) 1, 1-22 OLC Linguistik Show details 20 A modular approach to self-organization of robot control based on language instruction Wermter, Stefan; Elmshaw, Mark; Farrand, Simon In: Connection science. - Abingdon, Oxfordshire : Taylor & Francis 15 (2003) 2-3, 73-94 BLLDB Show details Page: 1 2

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