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The purpose of this work is to investigate the process of grammatical acquisition from data. In order to do that, a computational learning system is used, composed of a Universal Grammar with associated parameters, and a learning algorithm, following the Principles and Parameters Theory. The Universal Grammar is implemented as a Unification-Based Generalised Categorial Grammar, embedded in a default inheritance network of lexical types. The learning algorithm receives input from a corpus of spontaneous child-directed transcribed speech annotated with logical forms and sets the parameters based on this input. This framework is used as a basis to investigate several aspects of language acquisition. In this thesis I concentrate on the acquisition of subcategorisation frames and word order information, from data. The data to which the learner is exposed can be noisy and ambiguous, and I investigate how these factors a#ect the learning process. The results obtained show a robust learner converging towards the target grammar given the input data available. They also show how the amount of noise present in the input data a#ects the speed of convergence of the learner towards the target grammar. Future work is suggested for investigating the developmental stages of language acquisition as predicted by the learning model, with a thorough comparison with the developmental stages of a child. This is primarily a cognitive computational model of language learning that can be used to investigate and gain a better understanding of human language acquisition, and can potentially be relevant to the development of more adaptive NLP technology.

The emergence of human communication systems is typically investigated via 2 approaches with complementary strengths and weaknesses: naturalistic studies and computer simulations. This study was conducted with a method that combines these approaches. Pairs of participants played video games requiring communication. Members of a pair were physically separated but exchanged graphic signals through a medium that prevented the use of standard symbols (e.g., letters). Communication systems emerged and developed rapidly during the games, integrating the use of explicit signs with information implicitly available to players and silent behavior-coordinating procedures. The systems that emerged suggest 3 conclusions: (a) signs originate from different mappings; (b) sign systems develop parsimoniously; (c) sign forms are perceptually distinct, easy to produce, and tolerant to variations.

this paper I re-examine the case for distinguishing language-specific phonetics from phonology, and concludes that this move is unmotivated. It is feasible to account for 4 phonetic and phonological phenomena within a unified framework, and such a model is better able to account for the many similarities between phonetics and phonology. It is appropriate to distinguish components of grammar where the representations and principles operative in each component are fundamentally distinct, thus it is uncontroversial to distinguish phonology from syntax. It is difficult to justify a distinction between phonetics and phonology on these grounds. Phonetics and phonology are not obviously distinguished by the nature of the representations involved, or in terms of the phenomena they encompass. As far as representation is concerned, most of the primitives of phonological representation remain phonetically-based in the sense that features and timing units are provided with broadly phonetic definitions. This has the peculiar consequence that sound is represented twice in grammar: Once at a coarse level of detail in the phonology, and then again at a finer grain in the phonetics. Perhaps more significant is the fact that there are also substantial similarities between many phenomena which are conventionally classified as phonetic and those which are conventionally classified as phonological, for example coarticulation is similar in many respects to assimilation. The aim of this paper is to explore the idea that these parallels are best accounted for by analyzing both `phonetic' and `phonological' phenomena within a unified framework so the similar properties of the two can be derived from the same constraints. Unifying phonetics and phonology does not imply a denial of the distinct...

In recent years there have been significant advances in the field of Unsupervised Grammar Inference (UGI) for Natural Languages such as English or Dutch. This paper presents a broad range of UGI implementations, where we can begin to see how the theory has been put in to practise. Several mature systems are emerging, built using complex models and capable of deriving natural language grammatical phenomena. The range of systems is classified into: models based on Categorial Grammar (GraSp, CLL, EMILE); Memory Based Learning models (FAMBL, RISE); Evolutionary computing models (ILM, LAgts); and string-pattern searches (ABL, GB). An objectively measurable statistical comparison of performance Of the systems reviewed is not yet feasible. However, their merits and shortfalls are discussed, as well as a look at what the future has in store for UGI.

In this paper, I review arguments for and against the emergence and maintenance of an innate language acquisition device (LAD) via genetic assimilation. By a LAD, I mean nothing more or less than a learning mechanism which incorporates

In categorial systems with a fixed structural component, the learning problem comes down to finding the solution for a set of typeassignment equations. A hard-wired structural component is problematic if one want to address issues of structural variation. Our starting point is a type-logical architecture with separate modules for the logical and the structural components of the computational system. The logical component expresses invariants of grammatical composition; the structural component captures variation in the realization of the correspondence between form and meaning. Learning in this setting involves finding the solution to both the type-assignment equations and the structural equations of the language at hand. We develop a view on these two subtasks which pictures learning as a process moving through a two-stage cycle.

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this paper, I argue that the decorrelation argument does not undermine the account of the evolution of the language faculty via genetic assimilation nor the extended coevolutionary account in which the evolving language faculty in turn exerts linguistic selection pressure on languages (e.g. Deacon, 1997; Kirby, 1998)

An investment of effort over the last two years has begun to produce a wealth of data concerning computational psycholinguistic models of syntax acquisition. The data is generated by running simulations on a recently completed database of word 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 linguistically motivated by current syntactic theory and the sentence patterns have been validated as psychologically/developmentally plausible by checking their frequency of occurrence in corpora of child-directed speech. A small case-study simulation is also presented. 1