PhD A thought the results showed that delta features were important and that the TIMIT-trained network performed best across languages so far. They also observed that an MLP trained on the target task reduced errors, while one trained on a different task could hurt performance when the input features were well normalized. They thought the reasons for the language and noise effects were still unclear and needed more experiments.