A speech recognition system operates in a noisy factory environment. If the background noise level dramatically increases, which consequence follows for the acoustic model's signal processing?

💡 Explanation

Increased noise levels overwhelm the feature extraction process because the system struggles to differentiate between speech and noise. This degradation in signal-to-noise ratio leads to a higher word error rate; therefore, the accuracy decreases, rather than improving performance or reducing computational load.

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