1. A method of adapting a trained acoustic model, which was trained using first training data including speech data obtained over a near-field channel type, to process speech data obtained over a far-field channel type, the trained acoustic model comprising first parameters having respective first values established during training of the trained acoustic model using the first training data, wherein the trained acoustic model comprises a multi-layer neural network, the method comprising: using at least one computer processor to perform: obtaining second training data comprising speech data obtained over the far-field channel type without obtaining corresponding stereo data over the near-field channel type; and adapting the trained acoustic model to process speech data obtained over the far-field channel type by: augmenting the trained acoustic model with a transformation component configured to receive input derived from speech data obtained over the far-field channel type, apply a transformation to the input to obtain transformed input, and provide the transformed input as input to the trained acoustic model, the transformation component comprising second parameters and at least one network layer, wherein the transformation component is configured to linearly transform the input to obtain the transformed input, wherein the augmenting comprises coupling outputs of the at least one network layer of the transformation component to inputs of a first layer of the multi-layer neural network; and training the transformation component by using only the second training data to determine respective second values for the second parameters, wherein training the transformation component by using only the second training data to determine the respective second values for the second parameters comprises: comparing sequence data output by the trained acoustic model in response to the transformed input with an expected sequence data output; and adjusting the second values for the second parameters based on the comparison of the sequence data output and the expected sequence data output.