Overfitting occurs when an AI model learns the training data too closely, including noise and irrelevant patterns, resulting in poor performance on new or unseen data.
Voice AI developers prevent Overfitting by using diverse training data, validation datasets, regularization techniques, and continuous model evaluation to maintain reliable speech and language performance.