PhD A thought the results showed that delta features were important and that the TIMIT-trained network generally performed best. They also found that neural networks helped when trained on the target task or when feature normalization was poor, but could hurt performance on mismatched tasks. They felt the reasons for the language and noise effects were still unclear and required more experiments.