Reappraising Lexical Specificity in Children’s Early Syntactic Combinations

Reappraising Lexical Specificity in Children’s Early Syntactic Combinations Stewart M. McCauley (smm424@cornell.edu) Morten H. Christiansen (christiansen@cornell.edu) Department of Psychology, Cornell University, Ithaca, NY 14853 USA Abstract The flexibility and unbounded expressivity of our linguistic abilities is unparalleled in the biological world. Explaining how children acquire this fundamental aspect of human language is a key challenge for cognitive science. A recent corpus study by Yang (2013) has cast doubt on the lexical specificity of children’s productivity, as hypothesized by usage-based approaches. Focusing on determiner-noun combinations, he suggests that children possess an adult-like determiner category. In this paper, we show that Yang’s results may depend too heavily on an idealized notion of frequency distributions. We propose that these issues may be resolved by sidestepping sampling considerations and directly modeling children’s actual language processing. We therefore evaluate the abilities of two computational models to capture children's productions of determiner-noun combinations. The first model implements a probabilistic context-free grammar, which acquires statistical information incrementally. A second model, the Chunk-based Learner (CBL), provides a simple instantiation of item-based learning. CBL outperforms the rule-based model, successfully producing the vast majority of the determiner-noun combinations in a dense corpus of child speech. The results thus suggest that the case against lexical specificity in children’s early determiner-noun sequences may be overstated. Keywords: Language Learning; Grammatical Development; Computational Modeling; Usage-based Approaches; Sampling; Syntactic Categories; Lexical Specificity Introduction Much of the debate on language learnability has centered on the nature of children’s early productivity. Given the finite and noisy nature of the input, how are children able to generalize to a seemingly unbounded capacity for communicating novel information? The traditional answer invokes a system of words and rules, in which processing is memory-based at the word level, but algorithmic at the multiword level; compositional operations are performed over word classes corresponding to items from a mental lexicon (e.g., Chomsky, 1957; Pinker, 1999). Under this view, children are assumed to possess innate syntactic categories, such as noun and determiner. While various theoretical approaches differ with respect to the way in which innate word classes are mapped onto words themselves (e.g., Pinker, 1984), they converge on the idea that children’s early language use is—like adult language, under such a perspective—class-based. That is, children’s early comprehension and production abilities are governed by computations over their innate syntactic categories. In recent decades, a number of theoretical alternatives have emerged from the field of cognitive linguistics, such as construction grammar (e.g., Croft, 2001; Goldberg, 2006). Such approaches dispense with the words and rules framework entirely, holding instead that grammatical processing—and, by extension, children’s grammatical development—is primarily memory-based, driven by stored linguistic units of varying granularity and complexity. That is, knowledge of grammar is inseparable from lexical knowledge; the two can only be distinguished insofar as they constitute polar ends of a spectrum of unit complexity ranging from the level of simple symbols (such as morphemes and simple words) to complex symbols (such as grammatical constructions). While such approaches to explaining linguistic productivity allow syntactic categories to be learned, they do not converge on a single notion of the nature of such categorical knowledge (e.g., Croft, 2001), nor do they seek to directly explain the development of abstract categories themselves. They have, however, inspired developmental research in what has become known as the usage-based framework. A number of researchers in the usage-based tradition have identified item-based patterns in children’s early language use, such as verb-island phenomena (e.g., Tomasello, 1992). With respect to the development of abstract syntactic categories, a number of usage-based corpus studies have focused on the English determiner category as a test case, inspired by early proposals that the categorical knowledge driving children’s early speech is quite limited (e.g., Braine, 1976). In response to work arguing for an early abstract determiner category (e.g., Valian, 1986), Pine and Martindale (1996) analyzed seven corpora of child and child-directed speech. Controlling for the number of multi- word utterances in each sample, as well as vocabulary range, the authors found that children in the age range of 1;1 to 2;4 exhibited far less overlap in their determiner use than did their caretakers. Pine and Lieven (1997) extended this general finding to a group of 11 child corpora. Researchers have subsequently criticized the Pine and Martindale (1996) and Pine and Lieven (1997) studies for the sparseness of the data used as well as the inclusion of nouns that children produced with a determiner only once, making it impossible for there to be any overlap (e.g., Valian, Solt, & Stewart, 2009). More recently, Yang (2013) expanded on this criticism by noting that linguistic frequency distributions conform to a Zipfian pattern (Zipf, 1949), in which the frequency of a word is inversely proportional to its rank in a frequency table. Yang argued that such Zipfian patterns have the consequence that, even for adult speech, most nouns appear so infrequently in a corpus that they are unlikely to occur with more than one type of determiner. Yang used calculations based on Zipf’s