Michael Gasser

Topic continuity in discourse : a quantitative cross-language study

1. Topic continuity in discourse: An introduction (by Givon, T.) 2. Topic continuity in Japanese (by Hinds, John) 3. Topic continuity in written Amharic narrative (by Gasser, M.) 4. Topic continuity and word-order pragmatics in Ute (by Givon, T.) 5. Topic continuity in biblical Hebrew narrative (by Fox, A.) 6. Topic continuity and discontinuity in discourse: A study of spoken Latin-American Spanish (by Bentivoglio, Paola) 7. Topic continuity in written English narrative (by Brown, C.) 8. Topic continuity in spoken English (by Givon, T.) 9. Some dimensions of topic-NP continuity in Hausa narrative (by Jaggar, P.) 10. Topic continuity and the voicing system of an ergative language: Chamorro (by Cooreman, Ann) 11. Index of names

The Development of Embodied Cognition: Six Lessons from Babies

The embodiment hypothesis is the idea that intelligence emerges in the interaction of an agent with an environment and as a result of sensorimotor activity. We offer six lessons for developing embodied intelligent agents suggested by research in developmental psychology. We argue that starting as a baby grounded in a physical, social, and linguistic world is crucial to the development of the flexible and inventive intelligence that characterizes humankind.

Connectionism and Universals of Second Language Acquisition

This paper examines the implications of connectionist models of cognition for second language theory. Connectionism offers a challenge to the symbolic models which dominate cognitive science. In connectionist models all knowledge is embodied in a network of simple processing units joined by connections which are strengthened or weakened in response to regularities in input patterns. These models avoid the brittleness of symbolic approaches, and they exhibit rule-like behavior without explicit rules. A connectionist framework is proposed within which hypotheses about second language acquisition can be tested. Inputs and outputs are patterns of activation on units representing both form and meaning. Learning consists of the unsupervised association of pattern elements with one another. A network is first trained on a set of first language patterns and then exposed to a set of second language patterns with the same meanings. Several simulations of constituent-order transfer within this framework are discussed.

Learning nouns and adjectives : A connectionist account

Why do children learn nouns such as cup faster than dimensional adjectives such as big? Most explanations of this phenomenon rely on prior knowledge of the noun-adjective distinction or on the logical priority of nouns as the arguments of predicates. In this article we examine an alternative account, one which relies instead on properties of the semantic categories to be learned and of the word-learning task itself. We isolate four such properties: The relative size, the relative compactness, and the degree of overlap of the regions in representational space associated with the categories, and the presence or absence of lexical dimensions (what colour) in the linguistic context of a word. In a set of five experiments, we trained a simple connectionist network to label input objects in particular linguistic contexts. The network learned categories resembling nouns with respect to the four properties faster than it learned categories resembling adjectives.

The Acquisition of the lexicon

The nature of the mental lexicon, Edwin Williams and Beth Levin discovering the word units, Anne Cutler et al categorizing the world, Susan Carey and Frank C. Keil categories, words and language, Ellen M. Markman et al the case of verbs, Cynthia Fischer, D. Geoffrey Hall et al procedures for verb learning, Michael R. Brent et al.

Learning to Talk About the Properties of Objects: A Network Model of the Development of Dimensions

This chapter discusses that the protracted course of childrens acquisition of dimensional language, a lengthy process includes the acquisition of dimensional terms and the development of selective attention. It explains the developmental course by simulating it in a connectionist network. Results suggest that dimensions are created, that they are the product of learning dimensional language. The chapter discusses the idea of perceptual dimensions as the primitive atoms of experience have figured prominently in the study of cognition. It discusses that if perceptual dimensions are fixed and universal, then perception is bedrock on which language, knowledge, and truth can be built. If, in contrast, what is perceived and therefore what is knowable from ones own interactions with the world and, from the language one learns, then there is no single truth. What is knowable is relative. The dimensions that structure the conscious experience of the world are themselves the product of experience.

Meter as Mechanism: A Neural Network Model that Learns Metrical Patterns

One kind of prosodic structure that apparently underlies both music and some examples of speech production is meter. Yet detailed measurements of the timing of both music and speech show that the nested periodicities that define metrical structure can be quite noisy in time. What kind of system could produce or perceive such variable metrical timing patterns? And what would it take to be able to store and reproduce particular metrical patterns from long-term memory? We have developed a network of coupled oscillators that both produces and perceives patterns of pulses that conform to particular meters. In addition, beginning with an initial state with no biases, it can learn to prefer the particular meter that it has been previously exposed to.

Semitic Morphological Analysis and Generation Using Finite State Transducers with Feature Structures

This paper presents an application of finite state transducers weighted with feature structure descriptions, following Amtrup (2003), to the morphology of the Semitic language Tigrinya. It is shown that feature-structure weights provide an efficient way of handling the templatic morphology that characterizes Semitic verb stems as well as the long-distance dependencies characterizing the complex Tigrinya verb morphotactics. A relatively complete computational implementation of Tigrinya verb morphology is described.

Acquiring Receptive Morphology: A Connectionist Model

This paper describes a modular connectionist model of the acquisition of receptive inflectional morphology. The model takes inputs in the form of phones one at a time and outputs the associated roots and inflections. Simulations using artificial language stimuli demonstrate the capacity of the model to learn suffixation, prefixation, infixation, circumfixation, mutation, template, and deletion rules. Separate network modules responsible for syllables enable to the network to learn simple reduplication rules as well. The model also embodies constraints against association-line crossing.

Linguistic Introduction: The Orthography, Morphology and Syntax of Semitic Languages

We present in this chapter some basic linguistic facts about Semitic languages, covering orthography, morphology, and syntax. We focus on Arabic (both standard and dialectal), Ethiopian languages (specifically, Amharic), Hebrew, Maltese and Syriac. We conclude the chapter with a contrastive analysis of some of these phenomena across the various languages.