Time delay neural network

TDNN Diagram

Time delay neural network (TDNN) ^[1] 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^[2] implements that version.

See also

• 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.

References