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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 Hits 1 – 20 of 41 1 Cross-Situational Learning Towards Robot Grounding OOTA, Subba Reddy; Alexandre, Frédéric; Hinaut, Xavier In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022) BASE Show details 2 Cross-Situational Learning Towards Robot Grounding OOTA, Subba Reddy; Alexandre, Frédéric; Hinaut, Xavier In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022) BASE Show details 3 What does the Canary Say? Low-Dimensional GAN Applied to Birdsong Pagliarini, Silvia; Trouvain, Nathan; Leblois, Arthur... In: https://hal.inria.fr/hal-03244723 ; 2021 (2021) BASE Show details 4 What does the Canary Say? Low-Dimensional GAN Applied to Birdsong Pagliarini, Silvia; Trouvain, Nathan; Leblois, Arthur; Hinaut, Xavier In: https://hal.inria.fr/hal-03244723 ; 2021 (2021) Abstract: The generation of speech, and more generally complex animal vocalizations, by artificial systems is a difficult problem which has recently been addressed using various techniques in artificial intelligence. Generative Adversarial Networks (GANs) have shown very good abilities for generating images, and more recently sounds. The usability of a GAN generating a vocal repertoire relies in part on our understanding of the representations of the various sounds in the GAN latent space. Here, we aim to test the ability of WaveGAN to produce a set of canary syllables and constrain the latent space to a small dimension. We trained WaveGANs with varying latent space dimensions (from 1 to 6) on a large dataset of canary syllables (16000 renditions of 16 different syllable types). The sounds produced by the generators are identified and evaluated by a RNN-based classifier trained on the same dataset. This quantitative evaluation is paired with a qualitative evaluation of the GAN output spectrograms across GAN training epochs and latent dimensions, comparing multiple instances of the training for each condition. Altogether, our results show that a latent space of dimension 3 is enough to produce a varied repertoire of sounds of quality often indistinguishable from real canary ones, spanning all the types of syllables of the dataset. Importantly, we show that the 3-dimensional GAN generalizes by interpolating between the various syllable types. We rely on UMAP representations to qualitatively show the similarities between the training data and the generated data, and between the generated syllables and the interpolations produced. Exploring the latent representations of syllable types, we show that they form well identifiable subspaces of the latent space. This study provides tools to train simple sensorimotor models, as inverse models, from perceived sounds to motor representations of the same sounds. Both the RNN-based classifier and the small dimensional GAN provide a way to learn the mappings of perceived and produced sounds. 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]; [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]; Birdsong; Generative adversarial network; Latent space; Sound generation URL: https://hal.inria.fr/hal-03244723/file/Pagliarini2021_canary_GAN__HAL-v1.pdf https://hal.inria.fr/hal-03244723/document https://hal.inria.fr/hal-03244723 BASE Hide details 5 Which Hype for my New Task? Hints and Random Search for Reservoir Computing Hyperparameters Hinaut, Xavier; Trouvain, Nathan 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 6 Canary Song Decoder: Transduction and Implicit Segmentation with ESNs and LTSMs Trouvain, Nathan; Hinaut, Xavier In: https://hal.inria.fr/hal-03203374 ; 2021 (2021) BASE Show details 7 Which Hype for my New Task? Hints and Random Search for Reservoir Computing Hyperparameters Hinaut, Xavier; Trouvain, Nathan In: https://hal.inria.fr/hal-03203318 ; 2021 (2021) BASE Show details 8 Canary Song Decoder: Transduction and Implicit Segmentation with ESNs and LTSMs Trouvain, Nathan; Hinaut, Xavier 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 9 Hierarchical-Task Reservoir for Online Semantic Analysis from Continuous Speech Pedrelli, Luca; Hinaut, Xavier 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) BASE Show details 10 Editorial: Language and Robotics Taniguchi, Tadahiro; Horii, Takato; Hinaut, Xavier... 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) BASE Show details 11 Learning to Parse Sentences with Cross-Situational Learning using Different Word Embeddings Towards Robot Grounding ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Alexandre, Frédéric; Hinaut, Xavier. - : Underline Science Inc., 2021 BASE Show details 12 Cross-Situational Learning with Reservoir Computing for Language Acquisition Modelling Juven, Alexis; Hinaut, Xavier 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 13 Hierarchical-Task Reservoir for Anytime POS Tagging from Continuous Speech Pedrelli, Luca; Hinaut, Xavier In: 2020 International Joint Conference on Neural Networks (IJCNN 2020) ; https://hal.inria.fr/hal-02594495 ; 2020 International Joint Conference on Neural Networks (IJCNN 2020), Jul 2020, Glasgow, Scotland, United Kingdom ; https://wcci2020.org/ (2020) BASE Show details 14 Language Acquisition with Echo State Networks: Towards Unsupervised Learning Dinh, Thanh Trung; Hinaut, Xavier 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 15 A Journey in ESN and LSTM Visualisations on a Language Task Variengien, Alexandre; Hinaut, Xavier In: https://hal.inria.fr/hal-03030248 ; 2020 (2020) BASE Show details 16 Recurrent Neural Networks Models for Developmental Language Acquisition: Reservoirs Outperform LSTMs Hinaut, Xavier; Variengien, Alexandre 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 17 Learning to Parse Grounded Language using Reservoir Computing Hinaut, Xavier; Spranger, Michael 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) BASE Show details 18 Teach Your Robot Your Language! Trainable Neural Parser for Modelling Human Sentence Processing: Examples for 15 Languages Hinaut, Xavier; Twiefel, Johannes In: ISSN: 2379-8920 ; EISSN: 2379-8939 ; IEEE Transactions on Cognitive and Developmental Systems ; https://hal.inria.fr/hal-01964541 ; IEEE Transactions on Cognitive and Developmental Systems, Institute of Electrical and Electronics Engineers, Inc, 2019, ⟨10.1109/TCDS.2019.2957006⟩ ; https://doi.org/10.1109/tcds.2019.2957006 (2019) BASE Show details 19 A Reservoir Model for Intra-Sentential Code-Switching Comprehension in French and English Detraz, Pauline; Hinaut, Xavier 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 20 Replication of Laje & Mindlin's model producing synthetic syllables Zacchello, Jean-Baptiste; Hinaut, Xavier; Leblois, Arthur In: European Birdsong Meeting ; https://hal.inria.fr/hal-01964522 ; European Birdsong Meeting, Apr 2018, Odense, Denmark. 2018 (2018) BASE Show details Page: 1 2 3

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