42 citations · 157 across the 18 of their papers we have counts for
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cs.CL2025
Unsupervised Learning and Representation of Mandarin Tonal Categories by a Generative CNN
Kai Schenck, Gašper Beguš
This paper outlines the methodology for modeling tonal learning in fully unsupervised models of human language acquisition. Tonal patterns are among the computationally most comple…
cs.CL2025
Exploring the encoding of linguistic representations in the Fully-Connected Layer of generative CNNs for Speech
Bruno Ferenc Šegedin, Gasper Beguš
Interpretability work on the convolutional layers of CNNs has primarily focused on computer vision, but some studies also explore correspondences between the latent space and the o…