Page: 1 2 3 4 5 6 7 8 9... 205
81 |
Neural-based Knowledge Transfer in Natural Language Processing
|
|
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
87 |
Tackling Morphological Analogies Using Deep Learning -- Extended Version
|
|
|
|
In: https://hal.inria.fr/hal-03425776 ; 2021 (2021)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
93 |
Recognition of Grammatical Class of Imagined Words from EEG Signals using Convolutional Neural Network
|
|
|
|
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
|
|
BASE
|
|
Hide details
|
|
94 |
Deep Learning Methods for Human Behavior Recognition
|
|
Lu, Jia. - : Auckland University of Technology, 2021
|
|
BASE
|
|
Show details
|
|
95 |
Brain-Inspired Audio-Visual Information Processing Using Spiking Neural Networks
|
|
Wendt, Anne. - : Auckland University of Technology, 2021
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
100 |
What does the Canary Say? Low-Dimensional GAN Applied to Birdsong
|
|
|
|
In: https://hal.inria.fr/hal-03244723 ; 2021 (2021)
|
|
BASE
|
|
Show details
|
|
Page: 1 2 3 4 5 6 7 8 9... 205
|
|