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<Paper uid="J99-1001">
  <Title>A Process Model for Recognizing Communicative Acts and Modeling Negotiation Subdialogues</Title>
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1. Introduction
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    <Paragraph position="0"> In a typical expert-consultation dialogue, one participant (hereafter referred to as the executing agent or EA) has a goal that he 1 wants to achieve and is working with the other participant (referred to as the consulting agent or CA) to construct a plan for achieving this goal. Although both the plan construction process and the conversation are collaborative activities, this does not mean that people always believe what they are told. In fact, part of the collaborative activity of conversation is negotiation of conflicting beliefs. This negotiation is particularly important in task-oriented expert-consultation dialogues, since the participants must resolve any conflicting beliefs in order to work together effectively to devise a plan that is both well-formed and addresses the executing agent's needs. Thus, a robust natural language consultation system must be able to handle negotiation subdialogues.</Paragraph>
    <Paragraph position="1"> Even though there is wide agreement that negotiation is an integral part of multi-agent activity, previous natural language understanding systems have been unable to handle negotiation subdialogues such as the following:  (1) (2) $1: Who is teaching CS360? $2: Dr. Smith is teaching CS360.</Paragraph>
    <Paragraph position="2"> * Department of Computer Science, Newark, DE 19716, USA Department of Physics, Computer Science, and Engineering, Newport News, VA 23606, USA 1 For exposition purposes, we will use the masculine gender when referring to EA and the feminine gender when referring to CA.</Paragraph>
    <Paragraph position="3"> (~) 1999 Association for Computational Linguistics Computational Linguistics Volume 25, Number 1 (3) (4) (5) (6) $1: But isn't CS360 an undergraduate course? $2: Yes. CS360 is an undergraduate course.</Paragraph>
    <Paragraph position="4"> Dr. Smith teaches both graduate and undergraduate courses.</Paragraph>
    <Paragraph position="5"> $1: Who handles the CS360 lab?  For example, existing systems do not recognize when an agent is expressing doubt at a previous response as in utterance (3), when an agent is attempting to resolve a conflict suggested by the other participant as in utterances (4)-(5), or when an agent is implicitly conveying acceptance of a communicated proposition as in utterance (6). These shortcomings prevent existing natural language systems from being able to handle dialogues in which one agent initially does not accept the proposition conveyed by the other agent and initiates a negotiation subdialogue to resolve their differences in belief.</Paragraph>
    <Paragraph position="6"> We have developed a plan-based model of dialogue that addresses these limitations. Our analysis of naturally occurring dialogue indicates that one way that people express doubt at a proposition Pdoubt is by contending that some other conflicting proposition Pi is true. Our process model includes an algorithm for recognizing such expressions of doubt, as well as other complex discourse acts. The algorithm uses a multistrength belief model and a combination of linguistic, world, and contextual knowledge. Our implemented system can recognize implicit as well as explicit acceptance of a communicated proposition, multiple expressions of doubt at the same proposition, expressions of doubt at both immediately preceding and earlier utterances, and negotiation subdialogues embedded within other negotiation subdialogues. In the remainder of this paper, we describe our system and how this process is performed. Section 2 describes the kinds of expressions of doubt found in our corpus analysis, and Section 3 discusses the factors that must be taken into account in recognizing the kind of expression of doubt that we have been studying. Section 4 presents our process model for recognizing complex discourse acts (such as expressions of doubt) and assimilating them into the dialogue context. First it discusses why it is necessary to capture varying degrees of belief, describes the multistrength model of belief used in our system, and discusses how our description of actions avoids assuming that a speaker will automatically adopt a communicated proposition. Then it introduces the notion of an action that requires evidence for its recognition and presents our recognition algorithm that uses a combination of linguistic, world, and contextual knowledge. Section 5 steps through an extended example that illustrates our system's ability to recognize complex discourse acts and model negotiation subdialogues. Section 6 discusses the evaluation of our system and our plans for future work, and Section 7 discusses related research. The examples in this paper are taken from a university advisement domain, since this is the domain in which we have implemented our system.</Paragraph>
    <Paragraph position="7"> 2. Motivation from Naturally Occurring Dialogues To identify how speakers express doubt, we analyzed a corpus of naturally occurring dialogues in the domains of financial planning, university courses, real estate, pets, taxes, and travel. The real estate, pets, and financial planning (Harry Gross Transcripts 1982) dialogues were transcribed from radio talk shows, the taxes and travel (SRI Transcripts 1992) dialogues were transcribed from tapes of simulated interactions, and the university courses dialogues (Columbia University Transcripts, 1985) were Carberry and Lambert Modeling Negotiation Subdialogues transcribed from student advisement sessions. In the corpus we found instances in which a speaker expressed doubt at a proposition by contending that some other conflicting proposition was true. 2 In addition, we extracted other examples of such expressions of doubt from the dialogues in novels. These kinds of expressions of doubt can be realized as surface negative questions or tag questions and are often accompanied by the cue word but, as in the following example taken from the Harry Gross financial planning dialogues (Harry Gross Transcripts 1982) in which S2's last utterance expresses doubt at Sl's recommendation:  I would like to see that into an individual retirement account rollover in a mutual fund group.</Paragraph>
    <Paragraph position="8"> At my age? Yes.</Paragraph>
    <Paragraph position="9"> Uh, yeah but isn't there any risk? However, our corpus analysis also provided instances where surface negative and tag questions were used to seek verification, such as in the following excerpt from the set of financial planning dialogues: $1: $2: $1: And if you have more money left after you pay the taxes what difference does it make if you pay a few bucks more in taxes? I'm telling my wife but she won't listen.</Paragraph>
    <Paragraph position="10"> Well maybe she'll listen to me. If you get 200 bucks--isn't it better to have 200 bucks and uh have 200 left than to have nothing at all? Our recognition algorithm has only been concerned with recognizing instances in which a speaker expresses doubt by contending that some other proposition is true. However, in our corpus, speakers also expressed doubt in the following ways, and our future work will include extending our system to handle these: 3 Drawing attention to an inconsistent feature or proposition: The speaker brings into focus a feature or proposition that is already part of the dialogue context but that is intended to discredit the proposition being doubted. These utterances were often realized as an elliptical fragment and included &amp;quot;And you're how old?', &amp;quot;Even though it's four more years?&amp;quot;, and &amp;quot;At my age?&amp;quot; Drawing attention to violated expectations: The speaker mentions an expectation that is inconsistent with the doubted proposition. An example of this from our corpus is &amp;quot;You're kidding, what happened to the seventy-eight dollar fares or those sort of things ?&amp;quot; 2 We found a very few instances in which the speaker asked the hearer if he was sure the conflicting proposition wasn't true; an example from our corpus is &amp;quot;Are you sure he didn't name himself as attorney for the estate?&amp;quot; taken from the Harry Gross financial planning dialogues (Harry Gross Transcripts 1982). Our current system does not handle such expressions of doubt.</Paragraph>
    <Paragraph position="11"> 3 Walker (1996) analyzed the Harry Gross financial planning dialogues (Harry Gross Transcripts 1982) to identify features that distinguish acceptance from rejection. However, she did not consider expressions of doubt and some of her rejections would fall into our &amp;quot;express doubt&amp;quot; category.  has been said or asks for justification; examples from our corpus include &amp;quot;I'm not so sure of that.&amp;quot; and &amp;quot;Who ever said that?&amp;quot; * Cue words: The speaker uses discourse markers to convey his doubt. In addition to the cue word but that is often used to realize expressions of doubts in the other categories, cue words such as Really? and What? were used by themselves to express doubt and cue words such as even though were used to convey doubt in utterances such as &amp;quot;Even though it's four more years ?&amp;quot;</Paragraph>
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