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1
Le modèle Transformer: un « couteau suisse » pour le traitement automatique des langues
In: Techniques de l'Ingenieur ; https://hal.archives-ouvertes.fr/hal-03619077 ; Techniques de l'Ingenieur, Techniques de l'ingénieur, 2022, ⟨10.51257/a-v1-in195⟩ ; https://www.techniques-ingenieur.fr/base-documentaire/innovation-th10/innovations-en-electronique-et-tic-42257210/transformer-des-reseaux-de-neurones-pour-le-traitement-automatique-des-langues-in195/ (2022)
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2
VisSE corpus of Spanish SignWriting ...
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3
VisSE corpus of Spanish SignWriting ...
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4
Discovering latent social concepts across diverse societies
Gooyabadi, Maryam. - : eScholarship, University of California, 2021
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5
On Homophony and Rényi Entropy ...
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6
On Multi-domain Sentence Level Sentiment Analysis for Roman Urdu ...
Mehmood, Khawar. - : UNSW Sydney, 2021
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7
Generative Imagination Elevates Machine Translation ...
NAACL 2021 2021; Li, Lei; Long, Quanyu. - : Underline Science Inc., 2021
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8
Multilingual Email Zoning - Segmenting Multilingual Email Text Into Zones
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9
Contextualised sentiment analysis in the financial domain
Daudert, Tobias. - : NUI Galway, 2021
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10
ISL-CSLTR: Indian Sign Language Dataset for Continuous Sign Language Translation and Recognition ...
R, Elakkiya. - : Mendeley, 2021
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11
Content4All Open Research Sign Language Translation Datasets ...
CAMGOZ, NECATI CIHAN; BOWDEN, RICHARD. - : University of Surrey, 2021
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12
ISL-CSLTR: Indian Sign Language Dataset for Continuous Sign Language Translation and Recognition ...
R, Elakkiya. - : Mendeley, 2021
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13
Identity-Based Patterns in Deep Convolutional Networks: Generative Adversarial Phonology and Reduplication ...
Abstract: This papermodels unsupervised learning of an identity-based pattern (or copying) in speech called reduplication from raw continuous data with deep convolutional neural networks. We use the ciwGAN architecture (Beguˇs, 2021a) in which learning of meaningful representations in speech emerges from a requirement that the CNNs generate informative data. We propose a technique to wug-test CNNs trained on speech and, based on four generative tests, argue that the network learns to represent an identity-based pattern in its latent space. By manipulating only two categorical variables in the latent space, we can actively turn an unreduplicated form into a reduplicated form with no other substantial changes to the output in the majority of cases.We also argue that the network extends the identity-based pattern to unobserved data. Exploration of how meaningful representations of identity-based patterns emerge in CNNs and how the latent space variables outside of the training range correlate with identity-based patterns ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
URL: https://dx.doi.org/10.48448/j1k8-bt45
https://underline.io/lecture/38202-identity-based-patterns-in-deep-convolutional-networks-generative-adversarial-phonology-and-reduplication
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14
A Codicological and Linguistic Typology of Common Torah Codices from the Cairo Genizah ...
Arrant, Estara. - : Apollo - University of Cambridge Repository, 2021
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15
Signed Coreference Resolution ...
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16
Backtranslation in Neural Morphological Inflection ...
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17
Rule-based Morphological Inflection Improves Neural Terminology Translation ...
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18
Translating Headers of Tabular Data: A Pilot Study of Schema Translation ...
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19
A Prototype Free/Open-Source Morphological Analyser and Generator for Sakha ...
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20
Automatic Error Type Annotation for Arabic ...
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