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University of Copenhagen, Denmark
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CNNs can be made more interpretable without sacrificing too much accuracy by swapping the final layer for k-means and visualizing activations from multiple earlier blocks.
Semantic metrics and data cartography expose hidden biases in ASR systems that WER alone fails to capture, revealing a "diversity tax" on marginalized speakers.
