If a computational linguist aims to enhance a speech recognition system's resilience to accents using machine learning, which consequence follows?

💡 Explanation

Training a machine learning model on diverse accented speech improves the system's ability to generalize to new, unseen accents via statistical pattern recognition, because it builds a more robust acoustic model. Therefore, the model's generalization improves, rather than becoming simpler or needing fewer data, since diverse data leads to better generalization.

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