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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6 Hits 1 – 20 of 110 1 Artificial Intelligence in Digestive Endoscopy—Where Are We and Where Are We Going? Radu-Alexandru Vulpoi; Mihaela Luca; Adrian Ciobanu; Andrei Olteanu; Oana-Bogdana Barboi; Vasile Liviu Drug In: Diagnostics; Volume 12; Issue 4; Pages: 927 (2022) BASE Show details 2 Online And Face To Face Teaching: two complementary educational intervention modes ; L'enseignement du FLE en face à face et en ligne : deux modes d'intervention pédagogiques complémentaires Narainen, Stelene In: ISSN: 2773-286X ; Didaskein ; https://hal.archives-ouvertes.fr/hal-03429054 ; Didaskein, 2021, 2 (1), pp.28-47 (2021) BASE Show details 3 Reading Robot Watts, Gillian; Myers, Andrew; Tan, Sabrinna... In: General Engineering (2020) BASE Show details 4 Improving Mispronunciation Detection of Arabic Words for Non-Native Learners Using Deep Convolutional Neural Network Features Shamila Akhtar; Fawad Hussain; Fawad Riasat Raja; Muhammad Ehatisham-ul-haq; Naveed Khan Baloch; Farruh Ishmanov; Yousaf Bin Zikria In: Electronics ; Volume 9 ; Issue 6 (2020) Abstract: Computer-Aided Language Learning (CALL) is growing nowadays because learning new languages is essential for communication with people of different linguistic backgrounds. Mispronunciation detection is an integral part of CALL, which is used for automatic pointing of errors for the non-native speaker. In this paper, we investigated the mispronunciation detection of Arabic words using deep Convolution Neural Network (CNN). For automated pronunciation error detection, we proposed CNN features-based model and extracted features from different layers of Alex Net (layers 6, 7, and 8) to train three machine learning classifiers ; K-nearest neighbor (KNN), Support Vector Machine (SVM) and Random Forest (RF). We also used a transfer learning-based model in which feature extraction and classification are performed automatically. To evaluate the performance of the proposed method, a comprehensive evaluation is provided on these methods with a traditional machine learning-based method using Mel Frequency Cepstral Coefficients (MFCC) features. We used the same three classifiers KNN, SVM, and RF in the baseline method for mispronunciation detection. Experimental results show that with handcrafted features, transfer learning-based method and classification based on deep features extracted from Alex Net achieved an average accuracy of 73.67, 85 and 93.20 on Arabic words, respectively. Moreover, these results reveal that the proposed method with feature selection achieved the best average accuracy of 93.20% than all other methods. Keyword: computer-aided language learning; deep convolutional neural network; mel frequency cepstral coefficients (MFCC); mispronunciation detection; transfer learning URL: https://doi.org/10.3390/electronics9060963 BASE Hide details 5 Designing, translation: learning and evaluation of a Greek/English writing to Braille Aggelis, Alexandros In: Journal of Contemporary Education, Theory & Research ; 2 ; 16-21 (2020) BASE Show details 6 Artificial Intelligence and its future potential in lung cancer screening Joy Mathew, Christopher; David, Ashwini Maria; Joy Mathew, Chris Mariya. - : IfADo - Leibniz Research Centre for Working Environment and Human Factors, Dortmund, 2020 BASE Show details 7 Project-based learning: A practical approach to implementing Memsource in the classroom Herget, Katrin. - : Editorial Universitat Politècnica de València, 2020 BASE Show details 8 CALLIDUS -- Computer-Aided Language Learning: Lexikonerwerb im Lateinunterricht durch korpusgestützte Methoden ... Schulz, Konstantin. - : Zenodo, 2019 BASE Show details 9 CALLIDUS -- Computer-Aided Language Learning: Lexikonerwerb im Lateinunterricht durch korpusgestützte Methoden ... Schulz, Konstantin. - : Zenodo, 2019 BASE Show details 10 CALLIDUS: Intelligent Software Infrastructure for Teaching Latin ... Schulz, Konstantin. - : Zenodo, 2019 BASE Show details 11 CALLIDUS: Intelligent Software Infrastructure for Teaching Latin ... Schulz, Konstantin. - : Zenodo, 2019 BASE Show details 12 A vision of miking : Interactive programmatic modeling, sound language composition, and self-learning compilation Broman, David. - : KTH, Programvaruteknik och datorsystem, SCS, 2019. : Association for Computing Machinery, Inc, 2019 BASE Show details 13 Дистанционный курс письменной коммуникации по немецкому языку как иностранному Mueller, Julia Eduardovna In: Nauchnyy Dialog / Scientific Dialogue ; 10 ; 324-333 (2019) BASE Show details 14 Принципы организации смешанного курса по немецкому языку как иностранному на платформе Moodle Mueller, Julia Eduardovna In: Nauchnyy Dialog / Scientific Dialogue ; 4 ; 340-352 (2019) BASE Show details 15 Modeling language learning using specialized Elo ratings J. Hou; K. Maximilian; J.M. Hoya Quecedo. - : The Association for Computational Linguistics, 2019. : place:Stroudsburg, 2019 BASE Show details 16 CALLIDUS: Natural Language Processing and Empirical Studies for Teaching Latin ... Beyer, Andrea; Schulz, Konstantin. - : Zenodo, 2018 BASE Show details 17 CALLIDUS: Natural Language Processing and Empirical Studies for Teaching Latin ... Beyer, Andrea; Schulz, Konstantin. - : Zenodo, 2018 BASE Show details 18 COST ELN IS1401 Writing Support Tools Review Database Devitt, Ann. - : European Commission COST, 2018 BASE Show details 19 Phonological Feature Based Mispronunciation Detection and Diagnosis using Multi-Task DNNs and Active Learning Arora, V; Lahiri, A; Reetz, H. - 2017 BASE Show details 20 An investigation of changes in L2 writing anxiety between blended and conventional English language learning context Bailey, Daniel R.; Lee, Andrea Rakushin; Vorst, Tommy Che. - : Asia-Pacific Association for Computer-Assisted Language Learning, 2017 BASE Show details Page: 1 2 3 4 5 6

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