Observed arrival · 2026-10-23
CymaticBridge puts robot hearing to a fair test
An open experiment compares sound classification through a human-ear-inspired cochlea model with a standard mel-spectrogram approach.
- For
- Audio-ML researchers and robot-hearing builders
- Worth noticing
- The first reported ESC-50 test favors mel, 82.7% to 69.9%; the page says mel also stayed ahead under pink noise.
Field notes
The page lays out a controlled comparison: both listening systems use the same small network, training steps, and seed, with CARFAC cochlear features set against mel spectrograms. Its first reported test favors mel—82.7% versus 69.9% on ESC-50—and says mel also stayed ahead under pink noise. The log distinguishes pre-training from frozen-encoder classification tests and tracks later runs; the page says results refresh hourly, while the extracted snapshot shows overall completion at 0%.
Observed signals
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Editorial observations of this landing page, not a rating.
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