Time Delay Neural Network (TDNN) is part of a general class of dynamic networks, called focused networks, in which the dynamics appear only at the input layer of a static multilayer feedforward network. It is an artificial neural network architecture whose primary purpose is to work on sequential data. This architecture uses a modular and incremental design to create larger networks from sub components. It converting continuous audio into a stream of classified phoneme labels for speech recognition. TDNN has three layers of clusters, one for input, one for output, and the middle layer which handles manipulation of the input through filters.