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81
Neural-based Knowledge Transfer in Natural Language Processing
Wang, Chao. - 2022
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82
Temporal Emotion Dynamics in Social Networks
Naskar, Debashis. - : Universitat Politècnica de València, 2022
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83
Investigating alignment interpretability for low-resource NMT
In: ISSN: 0922-6567 ; EISSN: 1573-0573 ; Machine Translation ; https://hal.archives-ouvertes.fr/hal-03139744 ; Machine Translation, Springer Verlag, 2021, ⟨10.1007/s10590-020-09254-w⟩ (2021)
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84
The 2011 Tohoku Tsunami from the Sky: A Review on the Evolution of Artificial Intelligence Methods for Damage Assessment
In: ISSN: 2076-3263 ; Geosciences ; https://hal.archives-ouvertes.fr/hal-03168500 ; Geosciences, MDPI, 2021, ⟨10.3390/geosciences11030133⟩ (2021)
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85
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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86
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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87
Tackling Morphological Analogies Using Deep Learning -- Extended Version
In: https://hal.inria.fr/hal-03425776 ; 2021 (2021)
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88
Alternate Endings: Improving Prosody for Incremental Neural TTS with Predicted Future Text Input
In: Interspeech 2021 - 22nd Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03372802 ; Interspeech 2021 - 22nd Annual Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic. pp.3865-3869, ⟨10.21437/Interspeech.2021-275⟩ (2021)
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89
Ontology as neuronal-space manifold: Towards symbolic and numerical artificial embedding
In: KRHCAI 2021 Workshop on Knowledge Representation for Hybrid & Compositional AI @ KR2021 ; https://hal.inria.fr/hal-03360307 ; KRHCAI 2021 Workshop on Knowledge Representation for Hybrid & Compositional AI @ KR2021, Nov 2021, Hanoi, Vietnam (2021)
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90
Ontology as neuronal-space manifold: Towards symbolic and numerical artificial embedding
In: KRHCAI 2021 Workshop on Knowledge Representation for Hybrid & Compositional AI @ KR2021 ; https://hal.inria.fr/hal-03360307 ; KRHCAI 2021 Workshop on Knowledge Representation for Hybrid & Compositional AI @ KR2021, Nov 2021, Hanoi, Vietnam (2021)
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91
Ontology as neuronal-space manifold: Towards symbolic and numerical artificial embedding
In: KRHCAI 2021 Workshop on Knowledge Representation for Hybrid & Compositional AI @ KR2021 ; https://hal.inria.fr/hal-03360307 ; KRHCAI 2021 Workshop on Knowledge Representation for Hybrid & Compositional AI @ KR2021, Nov 2021, Hanoi, Vietnam (2021)
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92
Speaker Attentive Speech Emotion Recognition
In: Proccedings of interspeech 2021 ; Interspeech 2021 ; https://hal.archives-ouvertes.fr/hal-03554368 ; Interspeech 2021, Aug 2021, Brno, Czech Republic. pp.2866-2870, ⟨10.21437/interspeech.2021-573⟩ (2021)
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93
Recognition of Grammatical Class of Imagined Words from EEG Signals using Convolutional Neural Network
Datta, S; Boulgouris, NV. - : Elsevier BV, 2021
Abstract: © 2021 The Authors. In this paper we propose a framework using multi-channel convolutional neural network (MC-CNN) for recognizing the grammatical class (verb or noun) of covertly-spoken words from electroencephalogram (EEG) signals. Our proposed network extracts features by taking into account spatial, temporal, and spectral properties of the EEG signal. Further, sets of signals acquired from different regions of the brain are processed separately within the proposed framework and are subsequently combined at the classification stage. This approach enables the network to effectively learn discriminative features from the locations of the brain where imagined speech is processed. Our network was tested using challenging experiments, including cases where the test subject did not take part in system training. In our main application scenario, where no instance of a specific noun or verb was used during training, our method achieved 85.7% recognition. Further, our proposed method was evaluated on a publicly available EEG dataset and achieved recognition rate of 93.8% in binary classification. These results demonstrate the potential of our method.
Keyword: covert speech; electroencephalogram (EEG); imagined speech; Multi-Channel Convolutional Neural Network (MC-CNN)
URL: https://doi.org/10.1016/j.neucom.2021.08.035
https://bura.brunel.ac.uk/handle/2438/23082
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94
Deep Learning Methods for Human Behavior Recognition
Lu, Jia. - : Auckland University of Technology, 2021
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95
Brain-Inspired Audio-Visual Information Processing Using Spiking Neural Networks
Wendt, Anne. - : Auckland University of Technology, 2021
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96
Gender Bias in Neural Translation: a preliminary study ; Biais de genre dans un système de traduction automatique neuronale : une étude préliminaire
In: Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale ; Traitement Automatique des Langues Naturelles ; https://hal.archives-ouvertes.fr/hal-03265895 ; Traitement Automatique des Langues Naturelles, 2021, Lille, France. pp.11-25 ; https://talnrecital2021.inria.fr/ (2021)
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97
Developmental changes in neural letter‐selectivity: A 1‐year follow‐up of beginning readers
In: ISSN: 1363-755X ; EISSN: 1467-7687 ; Developmental Science ; https://hal.archives-ouvertes.fr/hal-02931200 ; Developmental Science, Wiley, 2021, 21 (1), pp.e12999. ⟨10.1111/desc.12999⟩ (2021)
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98
SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking
In: SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval ; https://hal.sorbonne-universite.fr/hal-03290774 ; SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul 2021, Virtual Event, Canada. pp.2288-2292, ⟨10.1145/3404835.3463098⟩ (2021)
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99
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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100
What does the Canary Say? Low-Dimensional GAN Applied to Birdsong
In: https://hal.inria.fr/hal-03244723 ; 2021 (2021)
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