Unrestricted English text can be converted to speech through the use of a look up table, or through a parallel feedforward network of deterministic processing units. Here, we reproduce the network structure used in NETtalk. Several experiments are carried out to determine which characteristics of the network are responsible for which learning behavior, and how closely that maps human speech development. The network is also trained with different levels of speech complexity, and with a second language. The results are shown to be highly dependent on statistical characteristics of the input.
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