Hyperparameter tuning is the process of adjusting configuration settings that control how an AI model learns and performs. These might include learning rate, number of layers, or batch size. In voice AI, tuning improves recognition accuracy, response time, and overall reliability. It’s a crucial step during model development or fine-tuning to ensure optimal performance for specific tasks or industries.
