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EMAKG: an enriched version of the Microsoft Academic Knowledge Graph ...
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EMAKG: an enriched version of the Microsoft Academic Knowledge Graph ...
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A Corpus-Based Sentence Classifier for Entity–Relationship Modelling
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In: Electronics; Volume 11; Issue 6; Pages: 889 (2022)
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A Deep Learning Approach for Repairing Missing Activity Labels in Event Logs for Process Mining
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In: Information; Volume 13; Issue 5; Pages: 234 (2022)
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Corona-Rechtsprechung des Bundesverfassungsgerichts (BVerfG-Corona) ...
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[R] Source Code der Corona-Rechtsprechung des Bundesverfassungsgerichts (BVerfG-Corona-Source) ...
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[R] Source Code der Corona-Rechtsprechung des Bundesverfassungsgerichts (BVerfG-Corona-Source) ...
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Corona-Rechtsprechung des Bundesverfassungsgerichts (BVerfG-Corona) ...
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Text mining at multiple granularity: leveraging subwords, words, phrases, and sentences
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Multi-National Topics Maps for Parliamentary Debate Analysis
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Assessing English language sentences readability using machine learning models
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In: PeerJ Comput Sci (2022)
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CorpusExplorer ; Eine Software zur korpuspragmatischen Analyse
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An Approach Utilizing Linguistic Features for Fake News Detection
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In: IFIP Advances in Information and Communication Technology ; 17th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI) ; https://hal.inria.fr/hal-03287679 ; 17th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Jun 2021, Hersonissos, Crete, Greece. pp.646-658, ⟨10.1007/978-3-030-79150-6_51⟩ (2021)
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La enseñanza de la traducción en contextos de dominio limitado de la L2: analítica visual para la optimización de la planificación y la intervención ...
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La enseñanza de la traducción en contextos de dominio limitado de la L2: analítica visual para la optimización de la planificación y la intervención ...
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CorpusExplorer ... : Eine Software zur korpuspragmatischen Analyse ...
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Identity-Based Patterns in Deep Convolutional Networks: Generative Adversarial Phonology and Reduplication ...
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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 ...
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Keyword:
Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
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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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