Modelling the Noise-Robustness of Infants’ Word Representations: The Impact of Previous Experience
Bergmann, C., Bosch, L. t., Fikkert, P., & Boves, L.
Modelling the Noise-Robustness of Infants’ Word Representations: The Impact of Previous Experience. PLoS One, 10
(7): e0132245. doi:10.1371/journal.pone.0132245.
During language acquisition, infants frequently encounter ambient noise. We present a computational model to address whether specific acoustic processing abilities are necessary to detect known words in moderate noise—an ability attested experimentally in infants. The model implements a general purpose speech encoding and word detection procedure. Importantly, the model contains no dedicated processes for removing or cancelling out ambient noise, and it can replicate the patterns of results obtained in several infant experiments. In addition to noise, we also addressed the role of previous experience with particular target words: does the frequency of a word matter, and does it play a role whether that word has been spoken by one or multiple speakers? The simulation results show that both factors affect noise robustness. We also investigated how robust word detection is to changes in speaker identity by comparing words spoken by known versus unknown speakers during the simulated test. This factor interacted with both noise level and past experience, showing that an increase in exposure is only helpful when a familiar speaker provides the test material. Added variability proved helpful only when encountering an unknown speaker. Finally, we addressed whether infants need to recognise specific words, or whether a more parsimonious explanation of infant behaviour, which we refer to as matching, is sufficient. Recognition involves a focus of attention on a specific target word, while matching only requires finding the best correspondence of acoustic input to a known pattern in the memory. Attending to a specific target word proves to be more noise robust, but a general word matching procedure can be sufficient to simulate experimental data stemming from young infants. A change from acoustic matching to targeted recognition provides an explanation of the improvements observed in infants around their first birthday. In summary, we present a computational model incorporating only the processes infants might employ when hearing words in noise. Our findings show that a parsimonious interpretation of behaviour is sufficient and we offer a formal account of emerging abilities.