Publications

Abstract

In their comment, Dell and O'Seaghdha (1991) adduced any effect on phonological probes for semantic alternatives to the activation of these probes in the lexical network. We argue that that interpretation is false and, in addition, that the model still cannot account for our data. Furthermore, and different from Dell and O'seaghda, we adduce semantic rebound to the lemma level, where it is so substantial that it should have shown up in our data. Finally, we question the function of feedback in a lexical network (other than eliciting speech errors) and discuss Dell's (1988) notion of a unified production-comprehension system.

Abstract

Comment on Sperber and Wilson

Abstract

In an earlier article (Levinson, 1987b), I raised the possibility that a Gricean theory of implicature might provide a systematic partial reduction of the Binding Conditions; the briefest of outlines is given in Section 2.1 below but the argumentation will be found in the earlier article. In this article I want, first, to show how that account might be further justified and extended, but then to introduce a radical alternative. This alternative uses the same pragmatic framework, but gives an account better adjusted to some languages. Finally, I shall attempt to show that both accounts can be combined by taking a diachronic perspective. The attraction of the combined account is that, suddenly, many facts about long-range reflexives and their associated logophoricity fall into place.

Abstract

This paper is one in a series that develops a pragmatic framework in loose confederation with Jay Atlas and Larry Horn: thus they may or may not be responsible for the ideas contained herein. Jay Atlas provided many comments which I have utilized or perverted as the case may be. The Australian data to which this framework is applied was collected with the financial and personal assistance of many people and agencies acknowledged separately below; but I must single out for special thanks John Haviland, who recommended the study of Guugu Yimidhirr anaphora to me and upon whose grammatical work on Guugu Yimidhirr this paper is but a minor (and perhaps flawed) elaboration. A grant from the British Academy allowed me to visit Haviland in September 1986 to discuss many aspects of Guugu Yimidhirr with him, and I am most grateful to the Academy for funding this trip and to Haviland for generously making available his time, his texts (from which I have drawn many examples, not always with specific acknowledgement) and most especially his expertise. Where I have diverged from his opinion I may well learn to regret it. I must also thank Nigel Vincent for putting me in touch with a number of recent relevant developments in syntax (only some of which I have been able to address) and for suggestions for numerous improvements. In addition, I have benefited immensely for comments on a distinct but related paper (Levinson, 1987) kindly provided by Jay Atlas, John Haviland, John Heritage, Phil Johnson-Laird, John Lyons, Tanya Reinhart, Emanuel Schegloff and an anonymous referee; and from comments on this paper by participants in the Cambridge Linguistics Department seminar where it was first presented (especial thanks to John Lyons and Huang Yan for further comments, and Mary Smith for a counter-example). Despite all this help, there are sure to be errors of data and analysis that I have persisted in. Aid in gathering the Australian data is acknowledged separately below.

Abstract

Although spontaneous speech occurs more frequently in most listeners’ experience than read speech, laboratory studies of human speech recognition typically use carefully controlled materials read from a script. The phonological and prosodic characteristics of spontaneous and read speech differ considerably, however, which suggests that laboratory results may not generalize to the recognition of spontaneous and read speech materials, and their response time to detect word-initial target phonemes was measured. Response were, overall, equally fast in each speech mode. However analysis of effects previously reported in phoneme detection studies revealed significant differences between speech modes. In read speech but not in spontaneous speech, later targets were detected more rapidly than earlier targets, and targets preceded by long words were detected more rapidly than targets preceded by short words. In contrast, in spontaneous speech but not in read speech, targets were detected more rapidly in accented than unaccented words and in strong than in weak syllables. An explanation for this pattern is offered in terms of characteristic prosodic differences between spontaneous and read speech. The results support claim from previous work that listeners pay great attention to prosodic information in the process of recognizing speech.

Abstract

Subjects named pictures while hearing distractor words that shared word-initial or word-final segments with the picture names or were unrelated to the picture names. The relative timing of distractor and picture presentation was varied. Compared with unrelated distractors, both types of related distractors facilitated picture naming under certain timing conditions. Begin-related distractors facilitated the naming responses if the shared segments began 150 ms before, at, or 150 ms after picture onset. By contrast, end-related distractors only facilitated the responses if the shared segments began at or 150 ms after picture onset. The results suggest that the phonological encoding of the beginning of a word is initiated before the encoding of its end.

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

Previous research comparing detection times for syllables and for phonemes has consistently found that syllables are responded to faster than phonemes. This finding poses theoretical problems for strictly hierarchical models of speech recognition, in which smaller units should be able to be identified faster than larger units. However, inspection of the characteristics of previous experiments’stimuli reveals that subjects have been able to respond to syllables on the basis of only a partial analysis of the stimulus. In the present experiment, five groups of subjects listened to identical stimulus material. Phoneme and syllable monitoring under standard conditions was compared with monitoring under conditions in which near matches of target and stimulus occurred on no-response trials. In the latter case, when subjects were forced to analyze each stimulus fully, phonemes were detected faster than syllables.

Abstract

In The Netherlands, grammar teaching is an especially important subject in the curriculum of children aged 10-15 for several reasons. However, in spite of all attention and time invested, the results are poor. This article describes the problems and our attempt to overcome them by developing an intelligent computational instructional environment consisting of: a linguistic expert system, containing a module representing grammar and spelling rules and a number of modules to manipulate these rules; a didactic module; and a student interface with special facilities for grammar and spelling. Three prototypes of the functionality are discussed: BOUWSTEEN and COGO, which are programs for constructing and analyzing Dutch sentences; and TDTDT, a program for the conjugation of Dutch verbs.

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

This paper is an attempt to show that given the available observations on the behaviour of negation and presuppositions there is no simpler explanation than to assume that natural language has two distinct negation operators, the minimal negation which preserves presuppositions and the radical negation which does not. The three-valued logic emerging from this distinction, and especially its model-theory, are discussed in detail. It is, however, stressed that the logic itself is only epiphenomenal on the structures and processes involved in the interpretation of sentences. Horn (1985) brings new observations to bear, related with metalinguistic uses of negation, and proposes a “pragmatic” ambiguity in negation to the effect that in descriptive (or “straight”) use negation is the classical bivalent operator, whereas in metalinguistic use it is non-truthfunctional but only pragmatic. Van der Sandt (to appear) accepts Horn's observations but proposes a different solution: he proposes an ambiguity in the argument clause of the negation operator (which, for him, too, is classical and bivalent), according to whether the negation takes only the strictly asserted proposition or covers also the presuppositions, the (scalar) implicatures and other implications (in particular of style and register) of the sentence expressing that proposition. These theories are discussed at some length. The three-valued analysis is defended on the basis of partly new observations, which do not seem to fit either Horn's or Van der Sandt's solution. It is then placed in the context of incremental discourse semantics, where both negations are seen to do the job of keeping increments out of the discourse domain, though each does so in its own specific way. The metalinguistic character of the radical negation is accounted for in terms of the incremental apparatus. The metalinguistic use of negation in denials of implicatures or implications of style and register is regarded as a particular form of minimal negation, where the negation denies not the proposition itself but the appropriateness of the use of an expression in it. This appropriateness negation is truth-functional and not pragmatic, but it applies to a particular, independently motivated, analysis of the argument clause. The ambiguity of negation in natural language is different from the ordinary type of ambiguity found in the lexicon. Normally, lexical ambiguities are idiosyncratic, highly contingent, and unpredictable from language to language. In the case of negation, however, the two meanings are closely related, both truth-conditionally and incrementally. Moreover, the mechanism of discourse incrementation automatically selects the right meaning. These properties are taken to provide a sufficient basis for discarding the, otherwise valid, objection that negation is unlikely to be ambiguous because no known language makes a lexical distinction between the two readings.

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

This paper presents a cognitive theory on the production and shaping of selfrepairs during speaking. In an extensive experimental study, a new technique is tried out: artificial elicitation of self-repairs. The data clearly indicate that two mechanisms for computing the shape of self-repairs should be distinguished. One is based on the repair strategy called reformulation, the second one on lemma substitution. W. Levelt’s (1983, Cognition, 14, 41- 104) well-formedness rule, which connects self-repairs to coordinate structures, is shown to apply only to reformulations. In case of lemma substitution, a totally different set of rules is at work. The linguistic unit of central importance in reformulations is the major syntactic constituent; in lemma substitutions it is a prosodic unit. the phonological phrase. A parametrization of the model yielded a very satisfactory fit between observed and reconstructed scores.

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).