PhD A thought the results showed that delta features were important and that the TIMIT-trained network performed best so far, though it was unclear why. They also observed that MLPs trained on the target task reduced error, while those trained on different tasks could make well-normalized features perform worse. For Italian, combining MSG with PLP added little or no benefit.