Time delay neural network
Time delay neural network (TDNN)  is an artificial neural network architecture whose primary purpose is to work on sequential data. The TDNN units recognise features independent of time-shift (i.e. sequence position) and usually form part of a larger pattern recognition system. Converting continuous audio into a stream of classified phoneme labels for speech recognition.
An input signal is augmented with delayed copies as other inputs, the neural network is time-shift invariant since it has no internal state.
The original paper presented a perceptron network whose connection weights were trained with the back-propagation algorithm, this may be done in batch or online. The Stuttgart Neural Network Simulator implements that version.
- Convolutional neural network - a convolutional neural net where the convolution is performed along the time axis of the data is very similar to a TDNN.
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