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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 Hits 1 – 17 of 17 1 Modeling speech recognition and synthesis simultaneously: Encoding and decoding lexical and sublexical semantic information into speech with no access to speech data ... Begus, Gasper. - : Open Science Framework, 2022 BASE Show details 2 Deep Sound Change ... Begus, Gasper. - : Open Science Framework, 2021 BASE Show details 3 Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales ... Andreas, Jacob; Beguš, Gašper; Bronstein, Michael M.. - : arXiv, 2021 BASE Show details 4 Identity-Based Patterns in Deep Convolutional Networks: Generative Adversarial Phonology and Reduplication ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Beguš, Gašper. - : Underline Science Inc., 2021 BASE Show details 5 Interpreting intermediate convolutional layers of CNNs trained on raw speech ... Beguš, Gašper; Zhou, Alan. - : arXiv, 2021 BASE Show details 6 Identity-Based Patterns in Deep Convolutional Networks: Generative Adversarial Phonology and Reduplication ... Begus, Gasper. - : Open Science Framework, 2021 BASE Show details 7 Interpreting intermediate convolutional layers in unsupervised acoustic word classification ... Beguš, Gašper; Zhou, Alan. - : arXiv, 2021 BASE Show details 8 Generative Adversarial Phonology: Modeling unsupervised phonetic and phonological learning with neural networks ... Beguš, Gašper. - : arXiv, 2020 BASE Show details 9 Local and non-local dependency learning and emergence of rule-like representations in speech data by Deep Convolutional Generative Adversarial Networks ... Beguš, Gašper. - : arXiv, 2020 Abstract: This paper argues that training GANs on local and non-local dependencies in speech data offers insights into how deep neural networks discretize continuous data and how symbolic-like rule-based morphophonological processes emerge in a deep convolutional architecture. Acquisition of speech has recently been modeled as a dependency between latent space and data generated by GANs in Beguš (2020b; arXiv:2006.03965), who models learning of a simple local allophonic distribution. We extend this approach to test learning of local and non-local phonological processes that include approximations of morphological processes. We further parallel outputs of the model to results of a behavioral experiment where human subjects are trained on the data used for training the GAN network. Four main conclusions emerge: (i) the networks provide useful information for computational models of speech acquisition even if trained on a comparatively small dataset of an artificial grammar learning experiment; (ii) local processes are ... : In press at Computer Speech & Language ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG URL: https://dx.doi.org/10.48550/arxiv.2009.12711 https://arxiv.org/abs/2009.12711 BASE Hide details 10 Identity-Based Patterns in Deep Convolutional Networks: Generative Adversarial Phonology and Reduplication ... Beguš, Gašper. - : arXiv, 2020 BASE Show details 11 Deep Sound Change: Deep and Iterative Learning, Convolutional Neural Networks, and Language Change ... Beguš, Gašper. - : arXiv, 2020 BASE Show details 12 Modeling unsupervised phonetic and phonological learning in Generative Adversarial Phonology ... Beguš, Gašper. - : University of Mass Amherst, 2020 BASE Show details 13 CiwGAN and fiwGAN: Encoding information in acoustic data to model lexical learning with Generative Adversarial Networks ... Beguš, Gašper. - : arXiv, 2020 BASE Show details 14 Generative Adversarial Phonology: Modeling Unsupervised Phonetic and Phonological Learning With Neural Networks Beguš, Gašper In: Front Artif Intell (2020) BASE Show details 15 Modeling unsupervised phonetic and phonological learning in Generative Adversarial Phonology Beguš, Gašper In: Proceedings of the Society for Computation in Linguistics (2020) BASE Show details 16 Unnatural Phonology: A Synchrony-Diachrony Interface Approach Beguš, Gašper. - 2018 BASE Show details 17 Relativna kronologija naglasnih pojavov govora Žirovske kotline poljanskega narečja ; The Relative Chronology of Word-Prosodic Phenomena in the Local Dialect of the Žiri Basin (Poljana Dialect) Beguš, Gašper. - : ZRC SAZU and Hall Center for the Humanities, 2011 BASE Show details

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