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<Paper uid="T75-2024">
  <Title>CONSIDERATIONSFOR COMPUTATIONAL THEORIES OF SPEAKING: SEVEN THINGS SPEAKERS DO</Title>
  <Section position="2" start_page="0" end_page="0" type="metho">
    <SectionTitle>
I. INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> Fundamental progress has to do with the reinterpretation of basic ideas.</Paragraph>
    <Paragraph position="1"> Whitehead The opinion which is fated to be ultimately agreed to by all who investigate it is what we mean by the truth and the object represented in this opinion is the real.</Paragraph>
    <Paragraph position="2"> C. Pierce Any discipline in the course of its maturation experiences identity crises in deciding what it is and where it is going. Often an initial commonality of interests, methods, and even disgruntlements hides an eventual diversity of purposes and goals. It is often at this time that self-conscious decisions have to be made regarding the overall scope and directions of its enterprises. To a limited degree, computational linguistics is beginning to experience its own birth pains. Bedfellows who did not seem so strange initially are beginning to appear progressively more so. Perhaps now is a time for stock taking and some preliminary self reflection.</Paragraph>
    <Paragraph position="3"> The principal intent of this paper is to sort out what I feel to be some of the more basic purposes of computational linguistic research, and then to discuss some of the explanatory requirements for one aspect of such research, the modeling of the human speaker. The bulk of the paper will focus upon some of the more basic issues in describing human speaking by a computational model.</Paragraph>
  </Section>
  <Section position="3" start_page="0" end_page="123" type="metho">
    <SectionTitle>
II. THE DUAL CHARACTER OF
LINGUISTIC RESEARCH
COMPUTATIONAL
</SectionTitle>
    <Paragraph position="0"> Superficially, what distinguishes computational lingustics from other hybrid forms of linguistic research (sociolinguistics, psycholinguistics, ethnolinguistics, generative linguistics, etc.) is the concern to represent linguistic descriptions in terms of computer programs. The common bond in computational linguistic research is the computer, or stated somewhat more broadly, the information processing approach. However, while this common interest does serve to distinguish this form of linguistic research from a growing number of others, it does, I believe, masque some more elemental differences over the purposes of using computer programs to describe language. There seem to me to be two complementary but ultimately different directions in computational linguistics; the  first is concerned primarily with improving and developing the software technology whereby computers can use and process natural language; under this heading would be machine translation, question and answering systems, automated secretaries, and assorted text processing systems; the second is concerned with using the computer as a means of developing an accurate and empirically valid computational model of the linguistic and cognitive behaviors of a human speaker. To date these two interests have been regarded as one; the rationale being that human beings and machines would use analogous mechanisms in their comprehension and generation of language to make the system work efficiently. But if one's goals are descriptive, then I don't feel that any such latitude is justified and that the use of different models and approaches should be justified with reference to certain theoretical criteria and empirical evidence--to the extent it is possible. This of course, is not to say, that the two branches of research, the technological and the descriptive, will not or should not share their results or influence one another. Only that they each have different objectives and hence different methodological and theoretical requirements.</Paragraph>
    <Paragraph position="1"> Having made the distinction between technological and descriptive forms of computational linguistics, I am now going to have to hedge a bit. Because, whereas both forms of research do differ with respect to specific research objectives, they do share a common meta-language and methodology, and are dependent upon that language for their success. I am now referring to the dependence of computational linguistics upon abstract theories of programming and computation. Yet even this distinction between the abstract and the applied modeling is not so clearcut, as practical programming requirements, such as language comprehension, affect the design of programming languages, and they in turn affect how specific problems are represented and understood. However, I suspect that as the field of computational linguistics matures, the descriptive and the technological forms of research are going to exert different selective pressures on computational theory to produce different types of programming languages, one being more specialized and efficient, and the other being more generalized and probably less &amp;quot;practical&amp;quot;. Yet here too a qualification is needed, for where the more general and human-like problem solving language is shown to have practical and technological uses, then it too will have a technological application.</Paragraph>
    <Paragraph position="2"> Therefore, any advance in improving a machine's facility with natural language would analogously constitute an advance in our understanding of human language behavior. The hedge word here, of course, is analogously, for it is not clear to me whether a program designed for very specialized and restricted purposes can be any more than superficially analagous to a human speaker. A simulated secretary for</Paragraph>
    <Paragraph position="4"> example has far fewer concerns than an actual secretary and therefore is designed and programmed for more specialized purposes. Moreover, and perhaps most significantly, the simulated secretary has no inherent intentionality of its own; it doesn't care what others think of it, it does not need to please, it isn't distracted, and it doesn't deplore chauvinism and resist demeaning requests.</Paragraph>
    <Paragraph position="5"> Certainly there are analogies between what the simulated and the real secretary do, as both perform similar clerical and linguistic tasks, but these similarities are quite few when compared to their dissimilarities.</Paragraph>
    <Paragraph position="6"> Moreover, it is highly questionnable whether the programming techniques and methods used to model this very restricted form of behavior can be easily generalized to other types of behavior. Most experience in artificial intelligence suggests the contrary. The point which I believe needs to be made is that while, yes, at some level, the information processing behavior of machines and programs is similar or analogous to that of human beings, that for the most part, this level is too general to be of much use in understanding human thought and speech at present. Hence, computational linguistics and artificial intelligence should begin to distinguish between those research goals that are technologically oriented and those that are intended to be descriptive of human action.</Paragraph>
    <Paragraph position="7"> For if one's goals are purely technological such as machine translation or a question and answering system, then one is certainly justified in using virtually any mechanism one wants.</Paragraph>
    <Paragraph position="8"> The problem is that in our ignorance of how higher order and unobservable human problem solving processes and mechanisms work, we have to rely upon experiments with abstract programming languages and simulated environments just to give us ideas about how such mechanisms might work. Certainly this is a reasonable strategy to pursue at this level of abstraction and experimentation.</Paragraph>
    <Paragraph position="9"> But when the intent then becomes the formulation of a computational model of some form of human activity, then I believe that there is a need to provide some theoretical or empirical justification for the model.</Paragraph>
    <Paragraph position="10"> For example, if the model is of a human interpreter of discourse, does the model make the same mistakes as people do, does it resolve ambiguity in the same way, can it make similar inferences from discourse as people, etc.? To answer these questions requires considerably more empirical evidence than we currently have.</Paragraph>
    <Paragraph position="11"> The real issue here is accountability.</Paragraph>
    <Paragraph position="12"> For programming languages and technological applications of computational linguistics this is relatively easy to determine. But when the intent is descriptive, that is, when a model is presented as representing some human intellectual skill or process, then the issue of accountability becomes murky indeed. For it is not enough to say that it works, or that expert judges cannot distinguish the model from the real thing; Weizenbaum's Eliza program showed how easy it is to attribute powers to the computer it  doesn't possess and Colby's indistinguishability tests have similarly shown the gullibility of trained psychiatrists. Consequently there is a need on the part of descriptive computational linguistics to both specify the types of tasks a model of a speaker or listener should perform and in addition, to the extent it is possible, the manner in which they should be performed.</Paragraph>
    <Paragraph position="13"> The problem then becomes knowing what it is one is wanting to describe and account for. And this is no easy matter, for as Wittgenstein noted (Wittgenstein, 1953), &amp;quot;the aspects of things that are most important for us are hidden because of their simplicity and familiarity (one is unable to notice something--because it is always before one s eyes).&amp;quot; Chomsky makes a similar point (Chomsky, 1970) &amp;quot;As native speakers we have a vast amount of data available to us.</Paragraph>
    <Paragraph position="14"> For this reason it is easy to fall into the trap of believing that there is nothing to be explained, that whatever organizing principles and underlying mechanisms may exist must be &amp;quot;given&amp;quot; as the data is given.&amp;quot; Traditionally linguists -- Chomsky among them -- have focussed upon the grammatical aspects of language usebecause it was so &amp;quot;given&amp;quot; and assumed that in accounting for the generation of grammatical utterances that they have in some way described at least some of the mechanisms involved in the generation of human speech. But as Max Black (Black, 1970), and a number of sociolinguists have pointed out (Hymes, 1972; Labov, 1974) to be able to characterize the grammaticality of a language with a finite set of rules does not mean that speakers of that language utilize such rules in their speaking. Therefore to my mind there is the real question of the value of such descriptions in accounting for either the individual or the collective use of language. Consequently when dealing even with the most obvious of linguistic &amp;quot;facts&amp;quot; there is a need to consider the more general role of language as a communicative, problem solving, and expressive medium. Similarly there is a need to characterize the type of explanation being sought; whether we want to explain language behavior in terms of reasons and intentions, or whether we want to describe it extentionally, in terms of causes.</Paragraph>
    <Paragraph position="15"> This latter distinction is one which Toulmin (Toulmin, 1970), Radnitsky (Radnitsky, 1970), Dennett (Dennett, 1975) and Goffman (Goffman, 1974), make in their varius dicussions of the types of explanations appropriate to the human or social sciences. Taking Toulmin's argument for the moment, causes are essentially like physical laws, as they are beyond our control, whereas &amp;quot;actions done for reasons can be regarded as applications of procedures (methods of calculation, techniques, rituals, or other formalized modes of behavior) that we have learned during our life time.&amp;quot; While ideally it may be possible to explain human language behavior in terms of causal descriptions, for example by neurological models, it is doubtful that this is the type of description that computational linguistics is seeking. Rather the appeal of the computational approach is precisely in its capacity to characterize the symbolic procedures that we use and have learned. If this orientation is accepted, then I believe that the obvious conclusion to be made is that language behavior should be described and explained as a learned intentional activity. Going one step further, then, one of its goals should bethe explanation of the various reasons and purposes for different types of linguistic behavior.</Paragraph>
    <Paragraph position="16"> However, to answer such questions satisfactorily requires a twofold description of the reasons for a procedural action. For taken from a historical or diachronic perspective, a given procedure is created to solve a particular set of problems at a particular time; hence its existence or reason for being is set in time. However, the same procedure may then again be used at some later time to achieve some other action perhaps unrelated to the first, and therefore has a reason independent of its derivation.</Paragraph>
    <Paragraph position="17"> Consequently, the reason a particular procedure was used can be explained in terms of the reason for its coming into being, or in terms of the immediate effect or result it was invoked to achieve. Psychotherapy is full of such cases: &amp;quot;Why do you smoke?&amp;quot; &amp;quot;Because I was bottle fed&amp;quot; or &amp;quot;Because I like the taste?&amp;quot; Similarly, for example, in understanding a speaker's use of intensifiers or dubitatives it is important to know whether they have a specific local meaning or whether they are a part of some standard discourse style -- either personal or cultural. For modeling purposes the differences are important, as they entail differences in representation.</Paragraph>
  </Section>
  <Section position="4" start_page="123" end_page="125" type="metho">
    <SectionTitle>
III. CONSIDERATIONS FOR A COMPUTATIONAL
THEORY OF SPEAKING
</SectionTitle>
    <Paragraph position="0"> So far we have established that that segment of computational linguistic research concerned with describing human speakers should take some initial steps towards saying more concretely what it is trying to account for. Certainly if we are going to evaluate a piece of research in this field, we should have some preliminary consensus as to what a successful model of speaking should be able to do. Likewise, there should be some common understanding as to the types of descriptions and explanations that are being sought.</Paragraph>
    <Paragraph position="1"> Taking the second question for the moment, I think that one of the unique contributions of a computationally based methodology to the human sciences is its capacity to give formal and .teleological descriptions to complex forms of symbolic behavior. Therefore one of the principal, if not inviolate, ingredients of a computational theory of speaking should be a computationally based methodology. This requirement would to my mind disqualify statistically based, and to a lesser extent, predicate calculus based, models.</Paragraph>
    <Paragraph position="2"> Furthermore, I feel that it is incumbent upon a modeler of human discourse to make  informed use of more advanced programming concepts, as problems resolved at this level eventually contribute a richer and more complete representation at the purely descriptive level. For example, although notions such as frames, mini-worlds, demons, actors, pattern matching and the like are essentially programming concepts, they do represent solutions or partial solutions to programming complex symbolic environments which in all likelihood are far simpler than those encountered by the everyday speaker.</Paragraph>
    <Paragraph position="3"> Consequently a computational model of speaking requires these techniques and methods both technically and theoretically. Now finally what a computational theory of speaking should in part, at least, account for. To date we seem to know very little about the types of mechanisms involved in the creation, formation, and regulation of speaking (here also, is included discourse and conversation). And while it would certainly be reassuring to compartmentalize speaking as a clearly bounded activity, both sociolinguists and phenomenologists have effectively dashed that hope.</Paragraph>
    <Paragraph position="4"> Since we can't say what speaking is -- if indeed it is any single thing (language does a disservice here), we can point out some of those things that people appear to do while speaking. It follows then that a model of human speaking should be able to do these too.</Paragraph>
    <Paragraph position="5"> Seven Thin~s Speakers Do I. People normally initiate a statement or a discourse out of a desire to be understood. They have some goal, or effect they want to achieve which they think speaking might facilitate.</Paragraph>
    <Paragraph position="6"> 2. Speakers alter what they are saying according to the physical and social context in which they are speaking. This in turn affects what is said and how it is said.</Paragraph>
    <Paragraph position="7"> 3. Speaker's have models of to whom they are speaking. They shape their remarks according to how they feel they are going to be interpreted. They apparently monitor what they are going to say, often making mistakes and changing their minds as they are speaking.</Paragraph>
    <Paragraph position="8"> 4. Speakers make effective use of the thematic organization of their conversations to direct interpretation, to specify role relationships, to qualify, intensify, and to amuse.</Paragraph>
    <Paragraph position="9"> 5. Speaking has a tone to it.</Paragraph>
    <Paragraph position="10"> Sometimes it is angry, other times placating. It can also be erudite, reverent, direct, evasive, sardonic, etc.</Paragraph>
    <Paragraph position="11">  constraints on what is said and how it is said; for example, Black narrative styles.</Paragraph>
    <Paragraph position="12"> 7. Speakers make effective use of idioms, &amp;quot;buzz words&amp;quot;, vernacular expressions, slang words to express themselves.</Paragraph>
    <Paragraph position="13"> Very likely most all these aspects of speaking appear as obvious, but to paraphrase the previous Wittgenstein quotation, it is often the obvious t~at escapes us. The argument can be made that yes, indeed, we will get to these things but let us first write a program that first speaks grammatically. I think that misses the point. Grammaticality is only one aspect of speaking behavior, and one which I doubt is as focal as it is made out to be. Grammar is just one of the means that speakers use to communicate their thoughts, intentions, and feelings to others. It should not be that element around which all subsequent investigations should be built. I feel that future work done with empirical data on speaking behavior will bear this point out and perhaps encourage the development of more comprehensive computational theories of speaking as an intentional and expressive human activity. If these theories are going to have a descriptive and explanatory value, they will at least have to be able to do these seven things that human speakers &amp;quot;obviously&amp;quot; do.</Paragraph>
  </Section>
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