PhD A thought the results showed that delta features were important and that the TIMIT-trained network generally performed best. MLPs improved recognition when trained on the target task, but could hurt performance on mismatched tasks unless the input features were poorly normalized. PhD A also thought MSG added little for Italian and that more experiments were needed to explain language and noise effects.