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If every productive form of linguistic expression can be described by some idealized human grammar, an individuals's variable linguistic behavior (Weinreich, Labov, & Herzog, 1968) can be modeled as a statistical distribution of multiple idealized grammars. The distribution of grammars is determined by the interaction between the biological constraints on human grammar and the properties of linguistic data in the environment during the course of language acquisition. Such interaction can be formalized precisely and quantitatively in a mathematical model of language learning. Consequently, we model language change as the change in grammar distribution over time, which can be related to the statistical properties of historical linguistic data. As an empirical test, we apply the proposed model to explain the loss of the verb-second phenomenon in Old French and Old English based on corpus studies of historical texts.

The present dissertation is a study of language development in children. From a biological perspective, the development of language, as the development of any other organic systems, is an interaction between internal and external factors; specifically, between the child's internal knowledge of linguistic structures and the external linguistic experience he receives. Drawing insights from the study of biological evolution, we put forth a quantitative model of language acquisition that make this interaction precise, by embedding a theory of knowledge, the Universal Grammar, into a theory of learning from experience. In particular, we advance the idea that language acquisition should be modeled as a population of grammatical hypotheses, competing to match the external linguistic experiences, much like in a natural selection process. We present evidenceconceptual, mathematical, and empirical, and from a number of independent areas of linguistic research, including the acquisition of syntax and morphophology, and historical language changeto demonstrate the model's correctness and utility.

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Understanding the evolution of language requires evidence regarding origins and processes that led to change. In the last 40 years, there has been an explosion of research on this problem as well as a sense that considerable progress has been made. We argue instead that the richness of ideas is accompanied by a poverty of evidence, with essentially no explanation of how and why our linguistic computations and representations evolved. We show that, to date, (1) studies of nonhuman animals provide virtually no relevant parallels to human linguistic communication, and none to the underlying biological capacity; (2) the fossil and archaeological evidence does not inform our understanding of the computations and representations of our earliest ancestors, leaving details of origins and selective pressure unresolved; (3) our understanding of the genetics of language is so impoverished that there is little hope of connecting genes to linguistic processes any time soon; (4) all modeling attempts have made unfounded assumptions, and have provided no empirical tests, thus leaving any insights into language's origins unverifiable. Based on the current state of evidence, we submit that the most fundamental questions about the origins and evolution of our linguistic capacity remain as mysterious as ever, with considerable uncertainty about the discovery of either relevant or conclusive evidence that can adjudicate among the many open hypotheses. We conclude by presenting some suggestions about possible paths forward.

How did language evolve? A popular approach points to the similarities between the ontogeny and phylogeny of language. Young children's language and nonhuman primates' signing both appear formulaic with limited syntactic combinations, thereby suggesting a degree of continuity in their cognitive abilities. To evaluate the validity of this approach, as well as to develop a quantitative benchmark to assess children's language development, I propose a formal analysis that characterizes the statistical profile of grammatical rules. I show that very young children's language is consistent with a productive grammar rather than memorization of specific word combinations from caregivers' speech. Furthermore, I provide a statistically rigorous demonstration that the sign use of Nim Chimpsky, the chimpanzee who was taught American Sign Language, does not show the expected productivity of a rule-based grammar. Implications for theories of language acquisition and evolution are discussed.computational linguistics | linguistics | primate cognition | psychology

We evaluate here the performance of four models of cross-situational word learning; two global models, which extract and retain multiple referential alternatives from each word occurrence; and two local models, which extract just a single referent from each occurrence. One of these local models, dubbed Pursuit, uses an associative learning mechanism to estimate word-referent probability but pursues and tests the best referent-meaning at any given time. Pursuit is found to perform as well as global models under many conditions extracted from naturalistic corpora of parent child-interactions, even though the model maintains far less information than global models. Moreover, Pursuit is found to best capture human experimental findings from several relevant cross-situational word-learning experiments, including those of Yu and Smith (2007), the paradigm example of a finding believed to support fully global cross-situational models. Implications and limitations of these results are discussed, most notably that the model characterizes only the earliest stages of word learning, when reliance on the co-occurring referent world is at its greatest.

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