Publications

Abstract

Eight experiments were carried out investigating whether different parts of a syllable must be phonologically encoded in a specific order or whether they can be encoded in any order. A speech production task was used in which the subjects in each test trial had to utter one out of three or five response words as quickly as possible. In the so-called homogeneous condition these words were related in form, while in the heterogeneous condition they were unrelated in form. For monosyllabic response words shorter reaction times were obtained in the homogeneous than in the heterogeneous condition when the words had the same onset, but not when they had the same rhyme. Similarly, for disyllabic response words, the reaction times were shorter in the homogeneous than in the heterogeneous condition when the words shared only the onset of the first syllable, but not when they shared only its rhyme. Furthermore, a stronger facilitatory effect was observed when the words had the entire first syllable in common than when they only shared the onset, or the onset and the nucleus, but not the coda of the first syllable. These results suggest that syllables are phonologically encoded in two ordered steps, the first of which is dedicated to the onset and the second to the rhyme.

Abstract

A patient who already had Wernick's aphasia due to a left temporal lobe lesion suffered a severe deterioration specifically of auditory language comprehension, subsequent to right temporal lobe infarction. A detailed comparison of his new condition with his language status before the second stroke revealed that the newly acquired deficit was limited to tasks related to auditory input. Further investigations demonstrated a speech perceptual disorder, which we analysed as due to deficits both at the level of general auditory processes and at the level of phonetic analysis. We discuss some arguments related to hemisphere specialization of phonetic processing and to the disconnection explanation of word deafness that support the hypothesis of word deafness being generally caused by mixed deficits.

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

The present experiment tested the suggestion that human listeners may exploit durational information in speech to parse continuous utterances into words. Listeners were presented with six-syllable unpredictable utterances under noise-masking, and were required to judge between alternative word strings as to which best matched the rhythm of the masked utterances. For each utterance there were four alternative strings: (a) an exact rhythmic and word boundary match, (b) a rhythmic mismatch, and (c) two utterances with the same rhythm as the masked utterance, but different word boundary locations. Listeners were clearly able to perceive the rhythm of the masked utterances: The rhythmic mismatch was chosen significantly less often than any other alternative. Within the three rhythmically matched alternatives, the exact match was chosen significantly more often than either word boundary mismatch. Thus, listeners both perceived speech rhythm and used durational cues effectively to locate the position of word boundaries.

Abstract

The roles which word class (open/closed) and sentential stress play in the sentence comprehension processes of both agrammatic (Broca's) aphasics and normal listeners were examined with a word monitoring task. Overall, normal listeners responded more quickly to stressed than to unstressed items, but showed no effect of word class. Aphasics also responded more quickly to stressed than to unstressed materials, but, unlike the normals, responded faster to open than to closed class words regardless of their stress. The results are interpreted as support for the theory that Broca's aphasics lack the functional underlying open/closed class word distinction used in word recognition by normal listeners.

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).