Two processes are used to grow the network. Discrimination adds a new node to the network, and familiarisation adds information to the node image. When an utterance is presented, each word in the utterance is considered in turn, which allows the utterance to be sorted to a given node. If the word currently considered has not previously been seen by the model, the process of discrimination is used to create a new node corresponding to that word. The new node is created at the first layer of the network, just below the root node.
Generative links are 'horizontal' links between nodes that have contextual similarities.
These two nodes do not have to be on the same level - a level 2 node can be linked to a level 3 node, for instance. These are produced by starting at each node in turn, and following the test links down the network. Production by generation utilises the generative links to create utterances not seen in the input. This occurs in a similar way to production by recognition, the difference being that lateral generative links can be traversed as well as vertical test links, although only one generative link can be followed per generated utterance. It is possible for some utterances to be produced by both recognition and generation.