A Word-Order Database for Testing Computational Models of Language Acquisition

A Word-Order Database for Testing Computational Models of Language Acquisition William Gregory Sakas Department of Computer Science PhD Programs in Linguistics and Computer Science Hunter College and The Graduate Center City University of New York sakas@hunter.cuny.edu Abstract An investment of effort over the last two years has begun to produce a wealth of data concerning computational psycholin- guistic models of syntax acquisition. The data is generated by running simulations on a recently completed database of word order patterns from over 3,000 abstract languages. This article presents the design of the database which contains sentence patterns, grammars and derivations that can be used to test acquisition models from widely divergent paradigms. The domain is generated from grammars that are lin- guistically motivated by current syntactic theory and the sentence patterns have been validated as psychologically/developmen- tally plausible by checking their frequency of occurrence in corpora of child-directed speech. A small case-study simulation is also presented. 1 Introduction The exact process by which a child acquires the grammar of his or her native language is one of the most beguiling open problems of cognitive science. There has been recent interest in computer simulation of the acquisition process and the interrelationship between such models and linguis- tic and psycholinguistic theory. The hope is that through computational study, certain bounds can be established which may be brought to bear on pivotal issues in developmental psycholinguistics. Simulation research is a significant departure from standard learnability models that provide results through formal proof (e.g., Bertolo, 2001; Gold, 1967; Jain et al., 1999; Niyogi, 1998; Niyogi & Berwick, 1996; Pinker, 1979; Wexler & Culi- cover, 1980, among many others). Although research in learnability theory is valuable and ongoing, there are several disadvantages to formal modeling of language acquisition: • Certain proofs may involve impractically many steps for large language domains (e.g. those involving Markov methods). • Certain paradigms are too complex to readily lend themselves to deductive study (e.g. con- nectionist models).1 • Simulations provide data on intermediate stages whereas formal proofs typically prove whether a domain is (or more often is not) learnable a priori to specific trials. • Proofs generally require simplifying assump- tions which are often distant from natural lan- guage. However, simulation studies are not without disadvantages and limitations. Most notable perhaps, is that out of practicality, simulations are typically carried out on small, severely circum- scribed domains – usually just large enough to allow the researcher to hone in on how a particular model (e.g. a connectionist network or a principles & parameters learner) handles a few grammatical features (e.g. long-distance agreement and/or topicalization) often, though not always, in a single language. So although there have been many successful studies that demonstrate how one algorithm or another is able to acquire some aspect of grammatical structure, there is little doubt that the question of what mechanism children actually employ during the acquisition process is still open. This paper reports the development of a large, multilingual database of sentence patterns, gram- 1 Although …

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