A convolutional neural network (CNN) trained for speech recognition misinterprets phonemes when exposed to audio with heavy reverb. Which mechanism explains this breakdown in encoding?

💡 Explanation

Temporal smearing, caused by reverb, interferes with the CNN's ability to accurately encode time-dependent features in speech because it blurs the distinct acoustic characteristics of phonemes. Therefore, feature encoding is disrupted, rather than simple overfitting or normalization problems.

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