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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)
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Canary Song Decoder: Transduction and Implicit Segmentation with ESNs and LTSMs
In: https://hal.inria.fr/hal-03203374 ; 2021 (2021)
Abstract: Domestic canaries produce complex vocal patterns embedded in various levels of abstraction. Studying such temporal organization is of particular relevance to understand how animal brains represent and process vocal inputs such as language. However, this requires a large amount of annotated data. We propose a fast and easy-to-train transducer model based on RNN architectures to automate parts of the annotation process. This is similar to a speech recognition task. We demonstrate that RNN architectures can be efficiently applied on spectral features (MFCC) to annotate songs at time frame level and at phrase level. We achieved around 95% accuracy at frame level on particularly complex canary songs, and ESNs achieved around 5% of word error rate (WER) at phrase level. Moreover, we are able to build this model using only around 13 to 20 minutes of annotated songs. Training time takes only 35 seconds using 2 hours and 40 minutes of data for the ESN, allowing to quickly run experiments without the need of powerful hardware.
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]; [SCCO.LING]Cognitive science/Linguistics; [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]; Audio Classification; Birdsong; Echo State Networks; Long Short Terms Memory; MFCC; RNN
URL: https://hal.inria.fr/hal-03203374/file/Trouvain2021_Canary-Song-Decoder_Hal-preprint-v1.pdf
https://hal.inria.fr/hal-03203374/document
https://hal.inria.fr/hal-03203374
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3
Which Hype for my New Task? Hints and Random Search for Reservoir Computing Hyperparameters
In: https://hal.inria.fr/hal-03203318 ; 2021 (2021)
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4
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)
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5
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)
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6
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)
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7
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)
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8
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)
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9
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)
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