PARSER: A model for word segmentation

Saffran, Newport, and Aslin (JML, 1996) showed that adults were able to segment into words an artificial language that included no pauses or other prosodic cues for word boundaries. We propose an account of their results that requires only limited computational abilities and memory capacity. In this account, parsing emerges as a natural consequence of the on-line attentional processing of the input, thanks to basic laws of memory and associative learning. Our account was implemented in a computer program, PARSER. Simulations revealed that PARSER extracted the words of the language well before exhausting the material presented to participants in the Saffran et al. experiments. In addition, PARSER was able to simulate the results obtained under attention-disturbing conditions (Saffran, Newport, Aslin, Tunick, & Barrueco, 1997) and those collected from 8-month-old infants (Saffran, Aslin, and Newport, Science 1996). Finally, the good performance of PARSER was not limited to the trisyllabic words used by Saffran et al., but also extended to a language composed of one- to five-syllable words.