How variable input shapes word recognition

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Word learning is a core part of language development - all other aspects of language intersect at the level of the word. And it is a surprisingly complex task. Word learners face two major categorization problems - in addition to determining the sets of objects in the world to which words should be mapped, they must also determine the set of tokens that constitute the same word. This is a difficult problem because no two instances of a word are acoustically identical. Some differences within and across speakers do not affect the meanings of words. However, when words are produced by speakers with different accents, changes can also occur along dimensions that alter the meanings of words. For example, when a French speaker produces the English word “pig”, it may sound to an English listener like the word “big”, because of differences in how the sounds “b” and “p” are produced in the two languages. Recent research has explored whether young listeners are able to recognize accented versions of familiar words. However, little is known about the more complex situation faced by language learners who are exposed to multiple word variants in their environment during the initial learning process. For example, if dad says “pig” and mom (who has a French accent) says something that sounds more like “big”, which version should be stored in the representation of that word? Should the child store both (perhaps tagged by speaker), just one (perhaps the one they hear most often), or something in between? Thus far, there have been only a few studies addressing the issue of how this type of variable input affects word representations and the findings have been inconsistent, with support for each of the above alternatives. The inconsistency of these findings is likely due in part to the fact that these studies involve different languages and types of accent variation, as well as different exposure situations. The goal of the present project is to further our understanding of how variable input affects word representations and processing by systematically manipulating input in the lab. The use of artificial languages to study other aspects of language learning has provided crucial insights into the nature of the information learners track in the input. This research will have significant theoretical and applied implications. First, it will provide insights into how input shapes the word recognition system and, more generally, the brain's capacity for handling multiple input systems simultaneously. Understanding how language input shapes learning is one of the most fundamental issues in the study of language development and variable-input situations provide a unique window on this issue. Second, this research has practical relevance, as children in today's global world are more and more likely to be exposed to multiple accents in the home, in school, or in the broader community.