A computational model of infant lexical stress preferences: Is the trochaic bias in English an emergent property of chunk learning?

<p>From early in development, children acquiring English as their first language show a preference for words with trochaic stress (strong-weak: doctor, candy, broken) compared to words with iambic stress (weak-strong: giraffe, police, forgot). Since children develop this trochaic bias as they become more familiar with English, it could be an emergent property of the statistical learning mechanisms that allow infants to discover words embedded in their continuous input. We tested this hypothesis using simulations with the CIPAL architecture, which represents the patterns it encounters by learning a diverse collection of chunks. The model was trained with samples of English child-directed speech, then presented with 24 trochaic and 24 frequency-matched iambic words. CIPAL showed a consistent preference for the trochaic items; they were more likely to be represented with single chunks in long-term memory, they were processed using fewer chunks, and they had faster processing times compared to the iambic items. CIPAL also demonstrated an iambic bias when the phonemes in the training samples were presented in reverse order, consistent with evidence that children’s stress preferences reflect the prosodic structure of their input. These results suggest that the trochaic bias in English can emerge through an incremental chunking process, which favours trochaic sequences because they are the most efficient way of processing English input.</p>