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1
The Impact of Game Elements on Learner Motivation: Influence of Initial Motivation and Player Profile
In: EISSN: 1939-1382 ; IEEE Transactions on Learning Technologies ; https://hal.univ-lyon2.fr/hal-03579428 ; IEEE Transactions on Learning Technologies, Institute of Electrical and Electronics Engineers, In press, ⟨10.1109/TLT.2022.3153239⟩ (2022)
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2
Human cumulative culture and the exploitation of natural phenomena
In: ISSN: 1471-2970 ; Philosophical Transactions of the Royal Society B: Biological Sciences ; https://hal.archives-ouvertes.fr/hal-03509412 ; Philosophical Transactions of the Royal Society B: Biological Sciences, 2022, 377 (1843), ⟨10.1098/rstb.2020.0311⟩ (2022)
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3
RETRIEVING SPEAKER INFORMATION FROM PERSONALIZED ACOUSTIC MODELS FOR SPEECH RECOGNITION
In: IEEE ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03539741 ; IEEE ICASSP 2022, 2022, Singapour, Singapore (2022)
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4
An investigation of English-Irish machine translation and associated resources
Dowling, Meghan. - : Dublin City University. School of Computing, 2022. : Dublin City University. ADAPT, 2022
In: Dowling, Meghan orcid:0000-0003-1637-4923 (2022) An investigation of English-Irish machine translation and associated resources. PhD thesis, Dublin City University. (2022)
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5
Cross-linguistic gender congruency effects during lexical access in novice L2 learners: evidence from ERPs
In: ISSN: 2327-3798 ; EISSN: 2327-3801 ; Language, Cognition and Neuroscience ; https://hal.archives-ouvertes.fr/hal-03599139 ; Language, Cognition and Neuroscience, Taylor and Francis, In press, ⟨10.1080/23273798.2022.2039726⟩ (2022)
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6
An Overview of Indian Spoken Language Recognition from Machine Learning Perspective
In: ISSN: 2375-4699 ; EISSN: 2375-4702 ; ACM Transactions on Asian and Low-Resource Language Information Processing ; https://hal.inria.fr/hal-03616853 ; ACM Transactions on Asian and Low-Resource Language Information Processing, ACM, In press, ⟨10.1145/3523179⟩ (2022)
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7
Hippocampal and auditory contributions to speech segmentation
In: ISSN: 0010-9452 ; Cortex ; https://hal.archives-ouvertes.fr/hal-03604957 ; Cortex, Elsevier, 2022, ⟨10.1016/j.cortex.2022.01.017⟩ (2022)
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8
The contextual logic
In: https://hal.archives-ouvertes.fr/hal-03195162 ; 2022 (2022)
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9
Is Old French tougher to parse?
In: 20th International Workshop on Treebanks and Linguistic Theories ; https://hal.archives-ouvertes.fr/hal-03506500 ; 20th International Workshop on Treebanks and Linguistic Theories, Mar 2022, Sofia, Bulgaria (2022)
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10
A Novel Multimodal Approach for Studying the Dynamics of Curiosity in Small Group Learning
In: https://hal.inria.fr/hal-03536340 ; 2022 (2022)
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11
Learning New Vocabulary Implicitly During Sleep Transfers With Cross-Modal Generalization Into Wakefulness
In: ISSN: 1662-4548 ; EISSN: 1662-453X ; Frontiers in Neuroscience ; https://hal.sorbonne-universite.fr/hal-03640595 ; Frontiers in Neuroscience, Frontiers, 2022, 16, pp.801666. ⟨10.3389/fnins.2022.801666⟩ (2022)
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12
Learning and controlling the source-filter representation of speech with a variational autoencoder
In: https://hal.archives-ouvertes.fr/hal-03650569 ; 2022 (2022)
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13
One model for the learning of language.
In: Proceedings of the National Academy of Sciences of the United States of America, vol 119, iss 5 (2022)
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14
Thirty Years of Machine Translation in Language Teaching and Learning: A Review of the Literature
In: L2 Journal, vol 14, iss 1 (2022)
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15
A review of Earth Artificial Intelligence
Sun, Z; Sandoval, L; Crystal-Ornelas, R. - : eScholarship, University of California, 2022
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16
Hippocampal ensembles represent sequential relationships among an extended sequence of nonspatial events.
In: Nature communications, vol 13, iss 1 (2022)
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17
Genetic Neural Architecture Search for automatic assessment of human sperm images
In: ISSN: 0957-4174 ; Expert Systems with Applications ; https://hal.archives-ouvertes.fr/hal-03585035 ; Expert Systems with Applications, Elsevier, 2022 (2022)
Abstract: International audience ; Male infertility is a disease that affects approximately 7% of men. Sperm morphology analysis (SMA) is one of the main diagnosis methods for this problem. However, manual SMA is an inexact, subjective, nonreproducible, and hard to teach process. Therefore, in this paper, we introduce a novel automatic SMA technique that is based on the neural architecture search algorithm, named Genetic Neural Architecture Search (GeNAS). For this purpose, we used a collection of images termed MHSMA dataset, which contains 1, 540 sperm images that have been collected from 235 patients with infertility problems. In detail, GeNAS consists of a special genetic algorithm that acts as a meta-controller which explores the constrained search space of plain convolutional neural network architectures. Every individual of this genetic algorithm is a convolutional neural network trained to predict morphological deformities in different segments of human sperm (head, vacuole, and acrosome). The fitness of each individual is calculated by a novel proposed method, named GeNAS Weighting Factor (GeNAS-WF). This technique is specially designed to evaluate the fitness of neural networks which, during their learning process, validation accuracy highly fluctuates. To speed up the algorithm, a hashing method is practiced to save each trained neural architecture fitness, so we could reuse them during fitness evaluation. In terms of running time and computational power, our proposed architecture search method is far more efficient than most of the other existing neural architecture search algorithms. Moreover, whereas most of the existing neural architecture search algorithms are designed to work well with well-prepared benchmark datasets, the overall paradigm of GeNAS is specially designed to address the challenges of real-world datasets, particularly shortage of data and class imbalance. In our experiments, the best neural architecture found by GeNAS has reached an accuracy of 91.66%, 77.33%, and 77.66% in the vacuole, head, and acrosome abnormality detection, respectively. In comparison to other proposed algorithms for MHSMA dataset, GeNAS achieved state-of-the-art results.
Keyword: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]; Deep Learning; Genetic Algorithm; Human Sperm Morphometry; Infertility; Neural Architecture Search
URL: https://hal.archives-ouvertes.fr/hal-03585035
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18
Assessing the impact of OCR noise on multilingual event detection over digitised documents
In: ISSN: 1432-5012 ; EISSN: 1432-1300 ; International Journal on Digital Libraries ; https://hal.archives-ouvertes.fr/hal-03635985 ; International Journal on Digital Libraries, Springer Verlag, 2022, ⟨10.1007/s00799-022-00325-2⟩ (2022)
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19
MAGIC DUST FOR CROSS-LINGUAL ADAPTATION OF MONOLINGUAL WAV2VEC-2.0
In: ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03544515 ; ICASSP 2022, May 2022, Singapour, Singapore (2022)
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20
Introducing the HIPE 2022 Shared Task: Named Entity Recognition and Linking in Multilingual Historical Documents
In: Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II ; https://hal.archives-ouvertes.fr/hal-03635971 ; Matthias Hagen; Suzan Verberne; Craig Macdonald; Christin Seifert; Krisztian Balog; Kjetil Nørvåg; Vinay Setty. Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II, 13186, Springer International Publishing, pp.347-354, 2022, Lecture Notes in Computer Science, 978-3-030-99738-0. ⟨10.1007/978-3-030-99739-7_44⟩ (2022)
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