Publications

Abstract

In his paper ‘On Horn's dilemma: presupposition and negation’ Burton-Roberts (1989a) presents an ambitious programme, formulated right at the outset. He seeks to establish three points: (i) Under the ‘standard logical definition of presupposition’ a pre-suppositional semantics is INCOMPATIBLE with a SEMANTICALLY AMBIGUOUS NEGATION operator (SAN), on pain of the theory being rendered ‘empirically empty and theoretically trivial’,. (ii) From this it follows that the one unambiguous negation is presupposition preserving. Cases that have been identified as presupposition-cancelling negation should be re-analysed as ‘instances of a pragmatic phenomenon’, not unlike what has been proposed in Horn (1985), that is as METALINGUISTIC NEGATION (MN). (iii) This pragmatic analysis of MN ‘itself implies a presuppositional semantics’, that is to say ‘a presuppositional theory of truth-value gaps’.

Abstract

Incremental sentence generation imposes special constraints on the representation of the grammar and the design of the formulator (the module which is responsible for constructing the syntactic and morphological structure). In the model of natural speech production presented here, a formalism called Segment Grammar is used for the representation of linguistic knowledge. We give a definition of this formalism and present a formulator design which relies on it. Next, we present an object- oriented implementation of Segment Grammar. Finally, we compare Segment Grammar with other formalisms.

Abstract

A quantitative model of human categorization behavior is proposed, which can be applied to 4-alternative forced-choice categorization data involving two binary classifications. A number of processing dependencies between the two classifications are explicitly formulated, such as the dependence of the location, orientation, and steepness of the class boundary for one classification on the outcome of the other classification. The significance of various types of dependencies can be tested statistically. Analyses of a data set from the literature shows that interesting dependencies in human speech recognition can be uncovered using the model.

Abstract

This study investigates whether spoken sentence comprehension deficits in Broca's aphasics results from their inability to access the subordinate meaning of ambiguous words (e.g. bank), or alternatively, from a delay in their selection of the contextually appropriate meaning. Twelve Broca's aphasics and twelve elderly controls were presented with lexical ambiguities in three context conditions, each followed by the same target words. In the concordant condition, the sentence context biased the meaning of the sentence final ambiguous word that was related to the target. In the discordant condition, the sentence context biased the meaning of the sentence final ambiguous word that was incompatible with the target.In the unrelated condition, the sentence-final word was unambiguous and unrelated to the target. The task of the subjects was to listen attentively to the stimuli The activational status of the ambiguous sentence-final words was inferred from the amplitude of the N399 to the targets at two inter-stimulus intervals (ISIs) (100 ms and 1250 ms). At the short ISI, the Broca's aphasics showed clear evidence of activation of the subordinate meaning. In contrast to elderly controls, however, the Broca's aphasics were not successful at selecting the appropriate meaning of the ambiguity in the short ISI version of the experiment. But at the long ISI, in accordance with the performance of the elderly controls, the patients were able to successfully complete the contextual selection process. These results indicate that Broca's aphasics are delayed in the process of contextual selection. It is argued that this finding of delayed selection is compatible with the idea that comprehension deficits in Broca's aphasia result from a delay in the process of integrating lexical information.

Abstract

This volume on Inuit speech follows the evolution of a native language of the North American Arctic, from its historical roots to its present-day linguistic structure and patterns of use from Alaska to Greenland. Drawing on a wide range of research from the fields of linguistics, anthropology, and sociology, Dorais integrates these diverse perspectives in a comprehensive view of native language development, maintenance, and use under conditions of marginalization due to social transition.

Abstract

This work presents a salvage grammar of the Biri language of Eastern Central Queensland, a Pama-Nyungan language belonging to the large Maric subgroup. As the language is no longer used, the grammatical description is based on old written sources and on recordings made by linguists in the 1960s and 1970s. Biri is in many ways typical of the Pama-Nyungan languages of Southern Queensland. It has split case marking systems, marking nouns according to an ergative/absolutive system and pronouns according to a nominative/accusative system. Unusually for its area, Biri also has bound pronouns on its verb, cross-referencing the person, number and case of core participants. As far as it is possible, the grammatical discussion is ‘theory neutral’. The first four chapters deal with the phonology, morphology, and syntax of the language. The last two chapters contain a substantial discussion of Biri’s place in the Pama-Nyungan family. In chapter 6 the numerous dialects of the Biri language are discussed. In chapter 7 the close linguistic relationship between Biri and the surrounding languages is examined.

Abstract

In normal conversation, speakers translate thoughts into words at high speed. To enable this speed, the retrieval of distinct types of linguistic knowledge has to be orchestrated with millisecond precision. The nature of this orchestration is still largely unknown. This report presents dynamic measures of the real-time activation of two basic types of linguistic knowledge, syntax and phonology. Electrophysiological data demonstrate that during noun-phrase production speakers retrieve the syntactic gender of a noun before its abstract phonological properties. This two-step process operates at high speed: the data show that phonological information is already available 40 milliseconds after syntactic properties have been retrieved.

Abstract

An essential phenomenon in the development towards syntactic maturity after early childhood is the increasing use of so-called sentence-combining transformations. Especially by using subordination, complex sentences are produced. The research reported here is an attempt to arrive at a more adequate characterization and explanation. Our starting point was an analysis of 280 texts written by Dutch-speaking pupils of the two highest grades of the primary school and the four lowest grades of three different types of secondary education. It was examined whether systematic shifts in the use of certain groups of so-called function words could be traced. We concluded that the development of the syntactic formulating ability can be characterized as an increase in connectivity: the use of all kinds of function words which explicitly mark logico-semantic relations between propositions. This development starts by inserting special adverbs and coordinating conjunctions resulting in various types of coordination. In a later stage, the syntactic patterning of the sentence is affected as well (various types of subordination). The increase in sentence complexity is only one aspect of the entire development. An explanation for the increase in connectivity is offered based upon a distinction between narrative and expository language use. The latter, but not the former, is characterized by frequent occurrence of connectives. The development in syntactic formulating ability includes a high level of skill in expository language use. Speed of development is determined by intensity of training, e.g. in scholastic and occupational settings.

Abstract

This paper reports two experiments with vowels and consonants as phoneme detection targets in real words. In the first experiment, two relatively distinct vowels were compared with two confusible stop consonants. Response times to the vowels were longer than to the consonants. Response times correlated negatively with target phoneme length. In the second, two relatively distinct vowels were compared with their corresponding semivowels. This time, the vowels were detected faster than the semivowels. We conclude that response time differences between vowels and stop consonants in this task may reflect differences between phoneme categories in the variability of tokens, both in the acoustic realisation of targets and in the' representation of targets by subjects.

Abstract

Computer simulations in an instructional context can be characterized according to four aspects (themes): simulation models, learning goals, learning processes and learner activity. The present paper provides an outline of these four themes. The main classification criterion for simulation models is quantitative vs. qualitative models. For quantitative models a further subdivision can be made by classifying the independent and dependent variables as continuous or discrete. A second criterion is whether one of the independent variables is time, thus distinguishing dynamic and static models. Qualitative models on the other hand use propositions about non-quantitative properties of a system or they describe quantitative aspects in a qualitative way. Related to the underlying model is the interaction with it. When this interaction has a normative counterpart in the real world we call it a procedure. The second theme of learning with computer simulation concerns learning goals. A learning goal is principally classified along three dimensions, which specify different aspects of the knowledge involved. The first dimension, knowledge category, indicates that a learning goal can address principles, concepts and/or facts (conceptual knowledge) or procedures (performance sequences). The second dimension, knowledge representation, captures the fact that knowledge can be represented in a more declarative (articulate, explicit), or in a more compiled (implicit) format, each one having its own advantages and drawbacks. The third dimension, knowledge scope, involves the learning goal's relation with the simulation domain; knowledge can be specific to a particular domain, or generalizable over classes of domains (generic). A more or less separate type of learning goal refers to knowledge acquisition skills that are pertinent to learning in an exploratory environment. Learning processes constitute the third theme. Learning processes are defined as cognitive actions of the learner. Learning processes can be classified using a multilevel scheme. The first (highest) of these levels gives four main categories: orientation, hypothesis generation, testing and evaluation. Examples of more specific processes are model exploration and output interpretation. The fourth theme of learning with computer simulations is learner activity. Learner activity is defined as the ‘physical’ interaction of the learner with the simulations (as opposed to the mental interaction that was described in the learning processes). Five main categories of learner activity are distinguished: defining experimental settings (variables, parameters etc.), interaction process choices (deciding a next step), collecting data, choice of data presentation and metacontrol over the simulation.

Abstract

The use of computer simulations in education and training can have substantial advantages over other approaches. In comparison with alternatives such as textbooks, lectures, and tutorial courseware, a simulation-based approach offers the opportunity to learn in a relatively realistic problem-solving context, to practise task performance without stress, to systematically explore both realistic and hypothetical situations, to change the time-scale of events, and to interact with simplified versions of the process or system being simulated. However, learners are often unable to cope with the freedom offered by, and the complexity of, a simulation. As a result many of them resort to an unsystematic, unproductive mode of exploration. There is evidence that simulation-based learning can be improved if the learner is supported while working with the simulation. Constructing such an instructional environment around simulations seems to run counter to the freedom the learner is allowed to in ‘stand alone’ simulations. The present article explores instructional measures that allow for an optimal freedom for the learner. An extensive discussion of learning goals brings two main types of learning goals to the fore: conceptual knowledge and operational knowledge. A third type of learning goal refers to the knowledge acquisition (exploratory learning) process. Cognitive theory has implications for the design of instructional environments around simulations. Most of these implications are quite general, but they can also be related to the three types of learning goals. For conceptual knowledge the sequence and choice of models and problems is important, as is providing the learner with explanations and minimization of error. For operational knowledge cognitive theory recommends learning to take place in a problem solving context, the explicit tracing of the behaviour of the learner, providing immediate feedback and minimization of working memory load. For knowledge acquisition goals, it is recommended that the tutor takes the role of a model and coach, and that learning takes place together with a companion. A second source of inspiration for designing instructional environments can be found in Instructional Design Theories. Reviewing these shows that interacting with a simulation can be a part of a more comprehensive instructional strategy, in which for example also prerequisite knowledge is taught. Moreover, information present in a simulation can also be represented in a more structural or static way and these two forms of presentation provoked to perform specific learning processes and learner activities by tutor controlled variations in the simulation, and by tutor initiated prodding techniques. And finally, instructional design theories showed that complex models and procedures can be taught by starting with central and simple elements of these models and procedures and subsequently presenting more complex models and procedures. Most of the recent simulation-based intelligent tutoring systems involve troubleshooting of complex technical systems. Learners are supposed to acquire knowledge of particular system principles, of troubleshooting procedures, or of both. Commonly encountered instructional features include (a) the sequencing of increasingly complex problems to be solved, (b) the availability of a range of help information on request, (c) the presence of an expert troubleshooting module which can step in to provide criticism on learner performance, hints on the problem nature, or suggestions on how to proceed, (d) the option of having the expert module demonstrate optimal performance afterwards, and (e) the use of different ways of depicting the simulated system. A selection of findings is summarized by placing them under the four themes we think to be characteristic of learning with computer simulations (see de Jong, this volume).