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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 Abstract: This paper presents a technique to interpret and visualize intermediate layers in CNNs trained on raw speech data in an unsupervised manner. We argue that averaging over feature maps after ReLU activation in each convolutional layer yields interpretable time-series data. By linearly interpolating individual latent variables to marginal levels outside of the training range, we further argue that we are able to observe a causal relationship between individual latent variables that encode linguistically meaningful units and activations in intermediate convolutional layers. The proposed technique allows acoustic analysis of intermediate layers that parallels the acoustic analysis of human speech data: we can extract F0, intensity, duration, formants, and other acoustic properties from intermediate layers in order to test where and how CNNs encode various types of information. Observing the causal effect between linear interpolation and the resulting changes in intermediate layers can reveal how individual ... Keyword: Artificial Intelligence cs.AI; Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Sound cs.SD URL: https://arxiv.org/abs/2104.09489 https://dx.doi.org/10.48550/arxiv.2104.09489 BASE Hide 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 BASE Show 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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