Shultz, T. R., Buckingham, D., & Oshima-Takane, Y. (1994). A connectionist model of the learning of personal pronouns in English. In S. J. Hanson, T. Petsche, M. Kearns, & R. L. Rivest (Eds.), Computational learning theory and natural learning systems, Vol. 2: Intersection between theory and experiment (pp. 347-362). Cambridge, MA: MIT Press.
Both experimental and observational psycholinguistic research have shown that children's acquisition of first and second person pronouns is affected by the opportunity to hear these pronouns used in speech not addressed to them. These effects were simulated with the cascade-correlation connectionist algorithm. The networks learned, in effect, to produce the pronouns me and you depending on identification of the speaker, addressee, and referent. Analysis of network performance and structure indicated that generalization to correct pronoun production was aided by listening to non-addressed speech and that persistent pronoun errors were created by listening to directly addressed speech. It was noted that explicit symbolic rule models would likely have difficulty simulating the pattern frequency effects common to the present simulations and to the natural language environment of the child.
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