Publications

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

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 introductory study of the perception of stochastically specified events is reported. The initial problem was to determine whether the perceiver can split visual input data of this kind into random and determined components. The inability of subjects to do so with the stimulus material used (a filmlike sequence of dot patterns), led to the more general question of how subjects code this kind of visual material. To meet the difficulty of defining the subjects' responses, two experiments were designed. In both, patterns were presented as a rapid sequence of dots on a screen. The patterns were more or less disturbed by “noise,” i.e. the dots did not appear exactly at their proper places. In the first experiment the response was a rating on a semantic scale, in the second an identification from among a set of alternative patterns. The results of these experiments give some insight in the coding systems adopted by the subjects. First, noise appears to be detrimental to pattern recognition, especially to patterns with little spread. Second, this shows connections with the factors obtained from analysis of the semantic ratings, e.g. easily disturbed patterns show a large drop in the semantic regularity factor, when only a little noise is added.

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).

Abstract

As a preliminary to further research on musical consonance an explanatory investigation was made on the different modes of judgment of musical intervals. This was done by way of a semantic differential. Subjects rated 23 intervals against 10 scales. In a factor analysis three factors appeared: pitch, evaluation and fusion. The relation between these factors and some physical characteristics has been investigated. The scale consonant-dissonant showed to be purely evaluative (in opposition to Stumpf's theory). This evaluative connotation is not in accordance with the musicological meaning of consonance. Suggestions to account for this difference have been given.