Modelling the phonotactic structure of natural language words with Simple Recurrent Networks

Simple Recurrent Networks (SRN) are Neural Network (connectionist) models able to process natural language. Phonotactics concerns the order of symbols in words. We continued an earlier unsuccessful trial to model the phonotactics of Dutch word corpus with SRNs. In order to overcome the previously reported obstacles, a new method for network testing was developed optimal threshold evaluation. This method is based on minimising the erroneous character prediction of a trained SRN. The network training was improved as well. The training words were presented to the network according to their frequencies, which emphasises the more frequent sequences. The achieved results are promising and provide a base for further study.