1 |
Cross-Situational Learning Towards Robot Grounding
|
|
|
|
In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
|
|
BASE
|
|
Show details
|
|
2 |
Cross-Situational Learning Towards Robot Grounding
|
|
|
|
In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
|
|
BASE
|
|
Show details
|
|
3 |
Which Hype for my New Task? Hints and Random Search for Reservoir Computing Hyperparameters
|
|
|
|
In: ICANN 2021 - 30th International Conference on Artificial Neural Networks ; https://hal.inria.fr/hal-03203318 ; ICANN 2021 - 30th International Conference on Artificial Neural Networks, Sep 2021, Bratislava, Slovakia (2021)
|
|
BASE
|
|
Show details
|
|
4 |
Canary Song Decoder: Transduction and Implicit Segmentation with ESNs and LTSMs
|
|
|
|
In: https://hal.inria.fr/hal-03203374 ; 2021 (2021)
|
|
BASE
|
|
Show details
|
|
5 |
Which Hype for my New Task? Hints and Random Search for Reservoir Computing Hyperparameters
|
|
|
|
In: https://hal.inria.fr/hal-03203318 ; 2021 (2021)
|
|
BASE
|
|
Show details
|
|
6 |
Canary Song Decoder: Transduction and Implicit Segmentation with ESNs and LTSMs
|
|
|
|
In: ICANN 2021 - 30th International Conference on Artificial Neural Networks ; https://hal.inria.fr/hal-03203374 ; ICANN 2021 - 30th International Conference on Artificial Neural Networks, Sep 2021, Bratislava, Slovakia. pp.71--82, ⟨10.1007/978-3-030-86383-8_6⟩ ; https://link.springer.com/chapter/10.1007/978-3-030-86383-8_6 (2021)
|
|
BASE
|
|
Show details
|
|
7 |
Cross-Situational Learning with Reservoir Computing for Language Acquisition Modelling
|
|
|
|
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)
|
|
BASE
|
|
Show details
|
|
8 |
Language Acquisition with Echo State Networks: Towards Unsupervised Learning
|
|
|
|
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)
|
|
BASE
|
|
Show details
|
|
9 |
Recurrent Neural Networks Models for Developmental Language Acquisition: Reservoirs Outperform LSTMs
|
|
|
|
In: SNL 2020 - 12th Annual Meeting of the Society for the Neurobiology of Language ; https://hal.inria.fr/hal-03146558 ; SNL 2020 - 12th Annual Meeting of the Society for the Neurobiology of Language, Oct 2020, Virtual Edition, Canada (2020)
|
|
BASE
|
|
Show details
|
|
10 |
A Reservoir Model for Intra-Sentential Code-Switching Comprehension in French and English
|
|
|
|
In: CogSci'19 - 41st Annual Meeting of the Cognitive Science Society ; https://hal.inria.fr/hal-02432831 ; CogSci'19 - 41st Annual Meeting of the Cognitive Science Society, Jul 2019, Montréal, Canada ; https://cognitivesciencesociety.org/cogsci-2019/ (2019)
|
|
BASE
|
|
Show details
|
|
11 |
An Empirical Study on Bidirectional Recurrent Neural Networks for Human Motion Recognition
|
|
Tanisaro, Pattreeya; Heidemann, Gunther. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2018. : LIPIcs - Leibniz International Proceedings in Informatics. 25th International Symposium on Temporal Representation and Reasoning (TIME 2018), 2018
|
|
BASE
|
|
Show details
|
|
12 |
Teach Your Robot Your Language! Trainable Neural Parser for Modelling Human Sentence Processing: Examples for 15 Languages
|
|
|
|
In: https://hal.inria.fr/hal-01665807 ; 2017 (2017)
|
|
Abstract:
We present a Recurrent Neural Network (RNN) that performs thematic role assignment and can be used for Human-Robot Interaction (HRI). The RNN is trained to map sentence structures to meanings (e.g. predicates). Previously, we have shown that the model is able to generalize on English and French corpora. In this study, we investigate its ability to adapt to various languages originating from Asia or Europe. We show that it can successfully learn to parse sentences related to home scenarios in fifteen languages: English, German, French, Spanish, Catalan, Basque, Portuguese, Italian, Bulgarian, Turkish, Persian, Hindi, Marathi, Malay and Mandarin Chinese. Moreover, in the corpora we have deliberately included variable complex sentences in order to explore the flexibility of the predicate-like output representations. This demonstrates that (1) the learning principle of our model is not limited to a particular language (or particular sentence structures), but more generic in nature, and (2) it can deal with various kind of representations (not only predicates), which enables users to adapt it to their own needs. As the model is inspired from neuroscience and language acquisition theories, this generic and language independent aspect makes it a good candidate for modelling human sentence processing. It is especially relevant when this model is implemented in grounded multimodal robotic architectures.
|
|
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; Artificial neural networks; echo state networks; human-robot interaction; language learning; multilingual; natural language processing; recurrent neural network; reservoir computing; sentence processing
|
|
URL: https://hal.inria.fr/hal-01665807
|
|
BASE
|
|
Hide details
|
|
13 |
Recurrent Neural Network for Syntax Learning with Flexible Predicates for Robotic Architectures
|
|
|
|
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
|
|
14 |
Recurrent Neural Network Sentence Parser for Multiple Languages with Flexible Meaning Representations for Home Scenarios
|
|
|
|
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)
|
|
BASE
|
|
Show details
|
|
17 |
On-Line Processing of Grammatical Structure Using Reservoir Computing
|
|
|
|
In: In A. E. P. Villa, et al.: Artificial Neural Networks and Machine Learning - ICANN 2012 - 22nd International Conference on Artificial Neural Networks ; https://hal.inria.fr/hal-02561301 ; In A. E. P. Villa, et al.: Artificial Neural Networks and Machine Learning - ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Sep 2012, Lausanne, Switzerland. pp.596-603, ⟨10.1007/978-3-642-33269-2_75⟩ (2012)
|
|
BASE
|
|
Show details
|
|
18 |
On-Line Processing of Grammatical Structure Using Reservoir Computing *
|
|
|
|
In: http://www.sbri.fr/files/publications/hinaut 12 icann.pdf
|
|
BASE
|
|
Show details
|
|
19 |
2007 Special Issue Learning grammatical structure with Echo State Networks
|
|
|
|
In: http://cs.ucsd.edu/%7Eechristiansen/papers/grammar_esn.pdf
|
|
BASE
|
|
Show details
|
|
|
|