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Generative Adversarial Phonology: Modeling Unsupervised Phonetic and Phonological Learning With Neural Networks

Training deep neural networks on well-understood dependencies in speech data can provide new insights into how they learn internal representations. This paper argues that acquisition of speech can be modeled as a dependency between random space and generated speech data in the Generative Adversarial...

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Bibliographische Detailangaben
Veröffentlicht in:Front Artif Intell
1. Verfasser: Beguš, Gašper
Format: Artigo
Sprache:Inglês
Veröffentlicht: Frontiers Media S.A. 2020
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Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7861218/
https://ncbi.nlm.nih.gov/pubmed/33733161
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/frai.2020.00044
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