42 citations · 157 across the 18 of their papers we have counts for
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cs.SD2021★ 5 cited
Interpreting intermediate convolutional layers in unsupervised acoustic word classification
Gašper Beguš, Alan Zhou
Understanding how deep convolutional neural networks classify data has been subject to extensive research. This paper proposes a technique to visualize and interpret intermediate l…
cs.SD2021
Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales
Jacob Andreas, Gašper Beguš, Michael M. Bronstein +16
The past decade has witnessed a groundbreaking rise of machine learning for human language analysis, with current methods capable of automatically accurately recovering various asp…
cs.SD2021★ 9 cited
Interpreting intermediate convolutional layers of generative CNNs trained on waveforms
Gašper Beguš, Alan Zhou
This paper presents a technique to interpret and visualize intermediate layers in generative CNNs trained on raw speech data in an unsupervised manner. We argue that averaging over…