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From Biological Synapses to “Intelligent” Robots
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In: ISSN: 2079-9292 ; Electronics ; https://hal.archives-ouvertes.fr/hal-03590998 ; Electronics, MDPI, 2022, 11 (5), pp.707. ⟨10.3390/electronics11050707⟩ (2022)
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| 2 |
Cross-Situational Learning Towards Robot Grounding
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In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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Cross-Situational Learning Towards Robot Grounding
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In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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Combining Bayesian and AI approaches for Autonomous Driving
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In: IROS 2021 - IEEE/RSJ International Conference on Intelligent Robots and Systems - Workshop "Perception and Navigation for Autonomous Robotics in Unstructured and Dynamic Environments" ; https://hal.inria.fr/hal-03518232 ; IROS 2021 - IEEE/RSJ International Conference on Intelligent Robots and Systems - Workshop "Perception and Navigation for Autonomous Robotics in Unstructured and Dynamic Environments", Sep 2021, Prague, Czech Republic (2021)
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| 5 |
Navigation In Urban Environments Amongst Pedestrians Using Multi-Objective Deep Reinforcement Learning
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In: ITSC 2021 - 24th IEEE International Conference on Intelligent Transportation Systems ; https://hal.inria.fr/hal-03372856 ; ITSC 2021 - 24th IEEE International Conference on Intelligent Transportation Systems, Sep 2021, Indianapolis, United States. pp.1-7 (2021)
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"It Is Not the Robot Who Learns, It Is Me." Treating Severe Dysgraphia Using Child-Robot Interaction
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In: ISSN: 1664-0640 ; Frontiers in Psychiatry ; https://hal.sorbonne-universite.fr/hal-03152170 ; Frontiers in Psychiatry, Frontiers, 2021, 12, pp.596055. ⟨10.3389/fpsyt.2021.596055⟩ (2021)
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| 7 |
Hierarchical-Task Reservoir for Online Semantic Analysis from Continuous Speech
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In: ISSN: 2162-237X ; IEEE Transactions on Neural Networks and Learning Systems ; https://hal.inria.fr/hal-03031413 ; IEEE Transactions on Neural Networks and Learning Systems, IEEE, 2021, ⟨10.1109/TNNLS.2021.3095140⟩ ; https://ieeexplore.ieee.org/abstract/document/9548713/metrics#metrics (2021)
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Abstract:
International audience ; In this paper, we propose a novel architecture called Hierarchical-Task Reservoir (HTR) suitable for real-time applications for which different levels of abstraction are available. We apply it to semantic role labeling based on continuous speech recognition. Taking inspiration from the brain, that demonstrates hierarchies of representations from perceptive to integrative areas, we consider a hierarchy of four sub-tasks with increasing levels of abstraction (phone, word, part-of-speech and semantic role tags). These tasks are progressively learned by the layers of the HTR architecture. Interestingly, quantitative and qualitative results show that the hierarchical-task approach provides an advantage to improve the prediction. In particular, the qualitative results show that a shallow or a hierarchical reservoir, considered as baselines, do not produce estimations as good asthe HTR model would. Moreover, we show that it is possible to further improve the accuracy of the model by designing skip connections and by considering word embedding in the internal representations. Overall, the HTR outperformed the other stateof-the-art reservoir-based approaches and it resulted in extremely efficient w.r.t. typical RNNs in deep learning (e.g. LSTMs). The HTR architecture is proposed as a step toward the modeling of online and hierarchical processes at work in the brain during language comprehension.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]; [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]; [SCCO.LING]Cognitive science/Linguistics; [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]; Anytime Process; Hierarchical Processing; Hierarchical Reservoir Computing; Natural Language Processing; Part-of-Speech; POS tagging; Recurrent Neural Networks; Semantic Role Labelling; Speech Recognition
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URL: https://hal.inria.fr/hal-03031413
https://doi.org/10.1109/TNNLS.2021.3095140
https://hal.inria.fr/hal-03031413v3/file/PedrelliHinaut2020_preprint_HAL-v3.pdf
https://hal.inria.fr/hal-03031413v3/document
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| 8 |
Editorial: Language and Robotics
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In: ISSN: 2296-9144 ; Frontiers in Robotics and AI ; https://hal.inria.fr/hal-03533733 ; Frontiers in Robotics and AI, Frontiers Media S.A., 2021, 8, ⟨10.3389/frobt.2021.674832⟩ (2021)
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| 9 |
Does the Goal Matter? Emotion Recognition Tasks Can Change the Social Value of Facial Mimicry towards Artificial Agents
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In: ISSN: 2296-9144 ; Frontiers in Robotics and AI ; https://hal.archives-ouvertes.fr/hal-03409678 ; Frontiers in Robotics and AI, Frontiers Media S.A., 2021, 8, ⟨10.3389/frobt.2021.699090⟩ (2021)
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| 10 |
From vocal prosody to movement prosody, from HRI to understanding humans
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In: VIHAR Vocal Interactivity in-and-between Humans, Animals and Robots ; https://hal.archives-ouvertes.fr/hal-03504825 ; VIHAR Vocal Interactivity in-and-between Humans, Animals and Robots, Oct 2021, Paris, France (2021)
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| 11 |
Comment les animaux et les robots transforment les relations ?
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In: Colloque international « Objets animés, humains, animaux : partenaires de soins tendres » ; https://hal.archives-ouvertes.fr/hal-03504819 ; Colloque international « Objets animés, humains, animaux : partenaires de soins tendres », Nov 2021, Grenoble, France (2021)
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| 12 |
Human communication and robotics
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In: VIHAR Vocal Interactivity in-and-between Humans, Animals and Robots ; https://hal.archives-ouvertes.fr/hal-03504822 ; VIHAR Vocal Interactivity in-and-between Humans, Animals and Robots, Oct 2021, Paris, France (2021)
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| 13 |
Insights into event representation from a sensorimotor model of event perception
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In: ICDL 2020 - 1st SMILES (Sensorimotor Interaction, Language and Embodiment of Symbols) workshop ; https://hal.archives-ouvertes.fr/hal-03202971 ; ICDL 2020 - 1st SMILES (Sensorimotor Interaction, Language and Embodiment of Symbols) workshop, Nov 2020, Valparaiso / Virtual, Chile ; https://sites.google.com/view/smiles-workshop/ (2020)
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| 14 |
Cross-Situational Learning with Reservoir Computing for Language Acquisition Modelling
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In: 2020 International Joint Conference on Neural Networks (IJCNN 2020) ; https://hal.inria.fr/hal-02594725 ; 2020 International Joint Conference on Neural Networks (IJCNN 2020), Jul 2020, Glasgow, Scotland, United Kingdom ; https://wcci2020.org/ (2020)
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| 15 |
Language Acquisition with Echo State Networks: Towards Unsupervised Learning
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In: ICDL 2020 - IEEE International Conference on Development and Learning ; https://hal.inria.fr/hal-02926613 ; ICDL 2020 - IEEE International Conference on Development and Learning, Oct 2020, Valparaiso / Virtual, Chile (2020)
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| 16 |
A Journey in ESN and LSTM Visualisations on a Language Task
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In: https://hal.inria.fr/hal-03030248 ; 2020 (2020)
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| 17 |
Mixing Bayesian and Artificial Intelligence approaches for Autonomous Driving
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In: Tech M&A 2019 - Minalogic Technical Conference ; https://hal.inria.fr/hal-02434275 ; Tech M&A 2019 - Minalogic Technical Conference, May 2019, Grenoble, France (2019)
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| 18 |
A journey in the history of Automated Driving
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In: IROS 2019 - IEEE/RSJ International Conference on Intelligent Robots and Systems ; https://hal.inria.fr/hal-02428196 ; IROS 2019 - IEEE/RSJ International Conference on Intelligent Robots and Systems, Nov 2019, Macau, China. pp.1-27 (2019)
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| 19 |
Learning to Parse Grounded Language using Reservoir Computing
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In: ICDL-Epirob 2019 - Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics ; https://hal.inria.fr/hal-02422157 ; ICDL-Epirob 2019 - Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics, Aug 2019, Olso, Norway. ⟨10.1109/devlrn.2019.8850718⟩ ; https://ieeexplore.ieee.org/abstract/document/8850718 (2019)
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| 20 |
Computer simulations of coupled idiosyncrasies in speech perception and speech production with COSMO, a perceptuo-motor Bayesian model of speech communication
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In: ISSN: 1932-6203 ; EISSN: 1932-6203 ; PLoS ONE ; https://hal.sorbonne-universite.fr/hal-01994708 ; PLoS ONE, Public Library of Science, 2019, 14 (1), pp.e0210302. ⟨10.1371/journal.pone.0210302⟩ (2019)
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