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1
DeepL et Google Translate face à l'ambiguïté phraséologique
In: https://hal.archives-ouvertes.fr/hal-03583995 ; 2022 (2022)
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2
A review of Earth Artificial Intelligence
Sun, Z; Sandoval, L; Crystal-Ornelas, R. - : eScholarship, University of California, 2022
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3
VEREINDEUTIGUNG ZUR KLASSIFIZIERUNG LEXIKALISCHER OBJEKTE ; DISAMBIGUATION FOR THE CLASSIFICATION OF LEXICAL ITEMS ; DÉSAMBÏGUISATION POUR LA CLASSIFICATION DE LEXÈMES
In: https://hal.archives-ouvertes.fr/hal-03598242 ; France, Patent n° : EP3937059A1. 2022 (2022)
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4
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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5
Cross-Situational Learning Towards Robot Grounding
In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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6
Cross-Situational Learning Towards Robot Grounding
In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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7
NewGen Libraries: The World of Artificial Intelligence ...
Chithra Ashok. - : Zenodo, 2022
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8
NewGen Libraries: The World of Artificial Intelligence ...
Chithra Ashok. - : Zenodo, 2022
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9
Structure and Learning (Dagstuhl Seminar 21362) ...
Dong, Tiansi; Rettinger, Achim; Tang, Jie. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022
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10
Emotional Speech Recognition Method Based on Word Transcription
In: Sensors; Volume 22; Issue 5; Pages: 1937 (2022)
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11
A Combined System Metrics Approach to Cloud Service Reliability Using Artificial Intelligence
In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 26 (2022)
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12
Situational Awareness: Techniques, Challenges, and Prospects
In: AI; Volume 3; Issue 1; Pages: 55-77 (2022)
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13
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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14
Innovative Vineyards Environmental Monitoring System Using Deep Edge AI
In: Artificial Intelligence for Digitising Industry Applications ; https://hal.univ-reims.fr/hal-03355270 ; Artificial Intelligence for Digitising Industry Applications, River Publishers, pp.261-278, 2021, 9788770226646 ; https://www.riverpublishers.com/research_details.php?book_id=967 (2021)
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15
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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16
Tackling Morphological Analogies Using Deep Learning -- Extended Version
In: https://hal.inria.fr/hal-03425776 ; 2021 (2021)
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17
Sentiment Analysis of Arabic Documents
In: Natural Language Processing for Global and Local Business ; https://hal.archives-ouvertes.fr/hal-03124729 ; Fatih Pinarbasi; M. Nurdan Taskiran. Natural Language Processing for Global and Local Business, pp.307-331, 2021, 9781799842408. ⟨10.4018/978-1-7998-4240-8.ch013⟩ ; https://www.igi-global.com/ (2021)
Abstract: International audience ; Today, it is usual that a consumer seeks for others' feelings about their purchasing experience on the web before a simple decision of buying a product or a service. Sentiment analysis intends to help people in taking profit from the available opinionated texts on the web for their decision making, and business is one of its challenging areas. Considerable work of sentiment analysis has been achieved in English and other Indo-European languages. Despite the important number of Arabic speakers and internet users, studies in Arabic sentiment analysis are still insufficient. The current chapter vocation is to give the main challenges of Arabic sentiment together with their recent proposed solutions in the literature. The chapter flowchart is presented in a novel manner that obtains the main challenges from presented literature works. Then it gives the proposed solutions for each challenge. The chapter reaches the finding that the future tendency will be toward rule-based techniques and deep learning, allowing for more dealings with Arabic language inherent characteristics.
Keyword: [INFO.EIAH]Computer Science [cs]/Technology for Human Learning; [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]; [INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]; [INFO.INFO-MC]Computer Science [cs]/Mobile Computing; [INFO.INFO-WB]Computer Science [cs]/Web; Arabic Language; Arabic NER; Arabizi; Corpus-based; Lexicon-based; NLP; Opinion Mining; Opinion Spam; Sentiment Analysis; Transliteration
URL: https://hal.archives-ouvertes.fr/hal-03124729
https://doi.org/10.4018/978-1-7998-4240-8.ch013
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18
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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19
What does the Canary Say? Low-Dimensional GAN Applied to Birdsong
In: https://hal.inria.fr/hal-03244723 ; 2021 (2021)
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20
What does the Canary Say? Low-Dimensional GAN Applied to Birdsong
In: https://hal.inria.fr/hal-03244723 ; 2021 (2021)
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