PhD A thought the results showed that delta features were important and that the TIMIT-trained network performed best so far. They also observed that neural networks helped when trained on the target task or when feature normalization was poor, but could reduce accuracy on different tasks when normalization was good. They felt more results were needed to determine the effects of language and noise, and suspected the poor MSG performance on Italian might have a simple cause.