Language Acquisition as Multiple-Cue Integration

The idea of language as shaped by the brain suggests that much of the neural hardware involved in language may not be specific to it. This means that language has to be acquired largely by mechanisms that are not uniquely dedicated for this purpose. In the second lecture, I propose that language has evolved to rely on a multitude of probabilistic information sources for its acquisition, allowing language to be as expressive as it is while still being learnable by domain-general learning mechanisms. I focus on the probabilistic contributions of phonological and distributional information to the learning of basic aspects of syntax. Based on results from corpus analyses, computational modeling and human experimentation, I argue that a probabilistic relationship exists between what a word sounds like and how it is used: nouns tend to sound like other nouns and verbs like other verbs. Importantly, these sources of phonological information, or “cues”, not only play an important role in language acquisition but also affect syntactic processing in adulthood. I conclude that the integration of phonological cues with other types of information is integral to the computational architecture of our language capacity. This integration, in turn, is what makes language learnable without universal grammar given the rich sources of information available in the input.