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1
Automatic Speech Recognition and Query By Example for Creole Languages Documentation
In: Findings of the Association for Computational Linguistics: ACL 2022 ; https://hal.archives-ouvertes.fr/hal-03625303 ; Findings of the Association for Computational Linguistics: ACL 2022, May 2022, Dublin, Ireland (2022)
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2
Cross-Situational Learning Towards Robot Grounding
In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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3
Cross-Situational Learning Towards Robot Grounding
In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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4
End-to-end speaker segmentation for overlap-aware resegmentation
In: Interspeech 2021 ; https://hal-univ-lemans.archives-ouvertes.fr/hal-03257524 ; Interspeech 2021, Aug 2021, Brno, Czech Republic ; https://www.interspeech2021.org/ (2021)
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5
High-resolution speaker counting in reverberant rooms using CRNN with Ambisonics features
In: EUSIPCO 2020 - 28th European Signal Processing Conference (EUSIPCO) ; https://hal.archives-ouvertes.fr/hal-03537323 ; EUSIPCO 2020 - 28th European Signal Processing Conference (EUSIPCO), Jan 2021, Amsterdam, Netherlands. pp.71-75, ⟨10.23919/Eusipco47968.2020.9287637⟩ (2021)
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6
Tackling Morphological Analogies Using Deep Learning -- Extended Version
In: https://hal.inria.fr/hal-03425776 ; 2021 (2021)
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7
Recognizing lexical units in low-resource language contexts with supervised and unsupervised neural networks
In: https://hal.archives-ouvertes.fr/hal-03429051 ; [Research Report] LACITO (UMR 7107). 2021 (2021)
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8
What does the Canary Say? Low-Dimensional GAN Applied to Birdsong
In: https://hal.inria.fr/hal-03244723 ; 2021 (2021)
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9
What does the Canary Say? Low-Dimensional GAN Applied to Birdsong
In: https://hal.inria.fr/hal-03244723 ; 2021 (2021)
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10
Artificial Text Detection via Examining the Topology of Attention Maps
In: ACL Anthology ; Empirical Methods in Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-03456191 ; Empirical Methods in Natural Language Processing, ACL (Association for Computational Linguistics), Nov 2021, Punta Cana, Dominican Republic (2021)
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11
Modeling the neural network responsible for song learning ; Modélisation du réseau neuronal responsable de l'apprentissage du chant chez l'oiseau chanteur
Pagliarini, Silvia. - : HAL CCSD, 2021
In: https://tel.archives-ouvertes.fr/tel-03217834 ; Modeling and Simulation. Université de Bordeaux, 2021. English. ⟨NNT : 2021BORD0107⟩ (2021)
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12
Multimodal Coarticulation Modeling : Towards the animation of an intelligible talking head ; Modélisation de la coarticulation multimodale : vers l'animation d'une tête parlante intelligible
Biasutto-Lervat, Théo. - : HAL CCSD, 2021
In: https://hal.univ-lorraine.fr/tel-03203815 ; Intelligence artificielle [cs.AI]. Université de Lorraine, 2021. Français. ⟨NNT : 2021LORR0019⟩ (2021)
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13
Impact of Segmentation and Annotation in French end-to-end Synthesis
In: Proc. 11th ISCA Speech Synthesis Workshop (SSW 11) ; SSW 11th ISCA Speech Synthesis Workshop ; https://hal.archives-ouvertes.fr/hal-03362000 ; SSW 11th ISCA Speech Synthesis Workshop, Aug 2021, Budapest, Hungary. pp.13-18, ⟨10.21437/SSW.2021-3⟩ ; https://ssw11.hte.hu/ (2021)
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14
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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15
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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16
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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17
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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18
On the use of Self-supervised Pre-trained Acoustic and Linguistic Features for Continuous Speech Emotion Recognition
In: IEEE Spoken Language Technology Workshop ; https://hal.archives-ouvertes.fr/hal-03003469 ; IEEE Spoken Language Technology Workshop, Jan 2021, Virtual, China (2021)
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19
Hierarchical-Task Reservoir for Online Semantic Analysis from Continuous Speech
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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20
Recognizing lexical units in low-resource language contexts with supervised and unsupervised neural networks
In: https://hal.archives-ouvertes.fr/hal-03429051 ; [Research Report] LACITO (UMR 7107). 2021 (2021)
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