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Which Input Abstraction is Better for a Robot Syntax Acquisition Model? Phonemes, Words or Grammatical Constructions?
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In: 2018 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) ; https://hal.inria.fr/hal-01889919 ; 2018 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), Sep 2018, Tokyo, Japan (2018)
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From Phonemes to Sentence Comprehension: A Neurocomputational Model of Sentence Processing for Robots
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In: SBDM2018 Satellite-Workshop on interfaces between Robotics, Artificial Intelligence and Neuroscience ; https://hal.inria.fr/hal-01964524 ; SBDM2018 Satellite-Workshop on interfaces between Robotics, Artificial Intelligence and Neuroscience, May 2018, Paris, France (2018)
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Neural coding of variable song structure in the songbird
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In: EBM 2017 - European Birdsong Meeting ; https://hal.inria.fr/hal-01665824 ; EBM 2017 - European Birdsong Meeting, May 2017, Bordeaux, France. pp.1 ; https://birdsong2017.sciencesconf.org/ (2017)
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| 24 |
From Phonemes to Robot Commands with a Neural Parser
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In: IEEE ICDL-EPIROB Workshop on Language Learning ; https://hal.inria.fr/hal-01665823 ; IEEE ICDL-EPIROB Workshop on Language Learning, Sep 2017, Lisbon, Portugal. pp.1-2 (2017)
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Modelling sentence processing with random recurrent neural networks and applications to robotics
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In: Workshop "The role of the basal ganglia in the interaction between language and other cognitive functions" ; https://hal.inria.fr/hal-01673440 ; Workshop "The role of the basal ganglia in the interaction between language and other cognitive functions", Anne-Catherine Bachoud-Lévi, Maria Giavazzi, Charlotte Jacquemot, Laboratoire de NeuroPsychologie Interventionnelle., Oct 2017, Paris, France ; http://www.ens.fr/agenda/role-basal-ganglia-interaction-between-language-and-other-cognitive-functions/2017-10 (2017)
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| 26 |
Syntactic Reanalysis in Language Models for Speech Recognition
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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)
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Teach Your Robot Your Language! Trainable Neural Parser for Modelling Human Sentence Processing: Examples for 15 Languages
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In: https://hal.inria.fr/hal-01665807 ; 2017 (2017)
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| 28 |
Recurrent Neural Network for Syntax Learning with Flexible Predicates for Robotic Architectures
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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)
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| 29 |
Recurrent Neural Network for Syntax Learning with Flexible Representations
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In: IEEE ICDL-EPIROB Workshop on Language Learning ; https://hal.inria.fr/hal-01417060 ; IEEE ICDL-EPIROB Workshop on Language Learning, Dec 2016, Cergy, France ; https://sites.google.com/site/epirob2016language/ (2016)
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| 30 |
Reservoir Computing for Robot Language Acquisition
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In: IROS Workshop on Machine Learning Methods for High-Level Cognitive Capabilities in Robotics ; https://hal.inria.fr/hal-01417683 ; IROS Workshop on Machine Learning Methods for High-Level Cognitive Capabilities in Robotics, Oct 2016, Daejon, South Korea ; http://mlhlcr2016.tanichu.com/home (2016)
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Abstract:
International audience ; How do children learn language? Could we use robots to model children language acquisition? This question is linked to a more general issue: how does the brain associate sequences of symbols to internal symbolic or sub-symbolic representations? I will present a Recurrent Neural Network (RNN), namely an Echo State Network (ESN) or Reservoir, that performs sentence comprehension and can be used for Human-Robot Interaction. The RNN is trained to map sentence structures to meanings (i.e. predicates). This model has interesting capabilities, for instance it can learn to "understand" French and English at the same time. Moreover, it is flexible and can be trained on different kinds of output predicate representations.The objective of this model is double: to improve HRI and provide neural models of language acquisition. From the HRI point of view, this model enables one (1) to gain adaptability because the system is trained on corpus examples (no need to predefine a parser for each language), (2) to be able to process natural language sentences instead of stereotypical sentences (i.e. "put cup left"), and (3) to be able to generalize to unknown sentence structures (not in the training data set). From the computational neuroscience and developmental robotics point of view, the aim of this architecture is to model and test hypotheses about child learning processes of language acquisition (Tomasello 2003).
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Keyword:
[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
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URL: https://hal.inria.fr/hal-01417683
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| 31 |
Recurrent Neural Network Sentence Parser for Multiple Languages with Flexible Meaning Representations for Home Scenarios
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In: IROS Workshop on Bio-inspired Social Robot Learning in Home Scenarios ; https://hal.inria.fr/hal-01417667 ; IROS Workshop on Bio-inspired Social Robot Learning in Home Scenarios, Oct 2016, Daejon, South Korea ; https://www.informatik.uni-hamburg.de/wtm/SocialRobotsWorkshop2016/index.php (2016)
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| 32 |
Semantic Role Labelling for Robot Instructions using Echo State Networks
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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)
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| 33 |
Using Natural Language Feedback in a Neuro-inspired Integrated Multimodal Robotic Architecture
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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)
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| 34 |
A Recurrent Neural Network for Multiple Language Acquisition: Starting with English and French
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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)
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| 35 |
Exploring the acquisition and production of grammatical constructions through human-robot interaction with echo state networks
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In: ISSN: 1662-5218 ; EISSN: 1662-5218 ; Frontiers in Neurorobotics ; https://hal.inria.fr/hal-02383530 ; Frontiers in Neurorobotics, Frontiers, 2014, 8, ⟨10.3389/fnbot.2014.00016⟩ (2014)
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| 36 |
Exploring the acquisition and production of grammatical constructions through human-robot interaction with echo state networks
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| 37 |
On-Line Learning of Lexical Items and Grammatical Constructions via Speech, Gaze and Action-Based Human-Robot Interaction
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In: INTERSPEECH 2013 - 14th Annual Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-02561340 ; INTERSPEECH 2013 - 14th Annual Conference of the International Speech Communication Association, Aug 2013, Lyon, France ; https://www.isca-speech.org/archive/interspeech_2013/i13_2657.html (2013)
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| 38 |
Real-Time Parallel Processing of Grammatical Structure in the Fronto-Striatal System: A Recurrent Network Simulation Study Using Reservoir Computing
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In: ISSN: 1932-6203 ; EISSN: 1932-6203 ; PLoS ONE ; https://hal.inria.fr/hal-01968923 ; PLoS ONE, Public Library of Science, 2013, 8 (2), pp.e52946. ⟨10.1371/journal.pone.0052946⟩ (2013)
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| 39 |
Real-Time Parallel Processing of Grammatical Structure in the Fronto-Striatal System: A Recurrent Network Simulation Study Using Reservoir Computing
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Online Language Learning to Perform and Describe Actions for Human-Robot Interaction
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In: Post-Graduate Conference on Robotics and Development of Cognition ; https://hal.inria.fr/hal-02561346 ; Post-Graduate Conference on Robotics and Development of Cognition, Sep 2012, Lausanne, Switzerland (2012)
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