DIKSIGN FOR I)IALOGUE COMPREHENSION 
William C. Mann 
USC Information Sciences Institute 
Marina del Rey, CA 
April, 1979 
This paper describes aspects of the design of a dialogue 
comprehension system, DCS, currently being Implemented. It 
concentrates on a few design innovations rather than the 
description of the whole system. The three areas of 
innovation discussed are: 
1. The relation of the DCS design to Speech Act theory 
and Dialogue Game theory, 
Z. Design assumptions about how to identify the "best" 
interpretation among several alternatives, and a 
method, called Preeminence Scheduling, for 
implementing those assumptions, 
3. A now control structure, tlearsay-3, that extends 
the control structure of llearsay-l\[ and makes 
Preeminence Scheduling fairly straightforward. 
I. Dialogue Games, Speech Acts and DCS -- Examination 
of actual human dialogue reveals structure extending over 
• ~overal turns and corresponding to partlcular issues that the 
participants raise and resolve. Our past work on dialogue has 
led to an account of this structure, Dialogue Game theory 
fLorin & Moore 1978; Moore, l,evlu & Mann 1977\]. This 
theory claims that dialogues (and other language uses as 
well) are comprehensible only because the participants are 
making available to each other the knowledge of the goals 
they are pursuing, at ~he p~omcnt, Patterns of these goals 
recur, representing language conventions: their theoretical 
representations are called Dialogue Games. 
If a speaker employs a particular Dialogue Game, that 
fact must be recognized by the hearer if the speaker is to 
achieve the desired effect. In other words, Dialogue Game 
recognition is an essential part of dialogue comprehension. 
Invoking a game is an act, and terminating the ongoing use 
of a game is also an act. 
Dialogue game theory has recently boon extended 
\[Mann 1079\] in a way makes these game-related acts 
explicit Acts of Bidding a game, Accepting a bid, and Bidding 
termination are formally defined as speech acts, comparable 
to others In speech act theory. So, for example, in the 
dialogue fragment below, 
Ct "Morn, l'm hungry." 
M." "Did you do a good Job on your Geography 
homework?" 
the first turn bids a game called the Permission Seeking 
game, and the second turn refuses that bid and bids the 
Information 5caking game. 
DCS is designed to recognize people's use of dialogue 
/~.ames in transcripts. For each utterance, it builds a 
hierarchlal structure representing how the utterance 
performs certain acts, the goals that the acts serve, end thn 
goal structure that makes the combination of acts coherent. 
(The data structure holding this information is described 
holow in the discussion of llearsay-3.) 
II. Preeminence Scheduling -- It seems inevitable that 
any system capable of forming the "correct" interpretation of 
most natural langua~,e usage will usually be able to find 
several other interpretations, given enough opportunity. It 
is also inevitable that choices bo made, implicitly or 
explicitly, among interpretations. The choices will 
correspond to some Internal notion of quality, also possibly 
implicit. The notion of quality may vary. but the necessity 
of makin/', such choices does not rest on the particular notion 
of quality we use. Clearly, it is also important to avoid 
choosing a single interpretation when there are several 
nearly equally attractive ones. 
What methods do we have for making such choices? 
Consider three approaches. 
I. First-find.. The first Interpretation discovered 
which satisfies well-formcdness is chosen. The 
effectiveness of first-find depends on having 
well-informed, selective processes at every choice 
point, and is only reasonable if one's expectations 
about what might be said are very good. Even then, 
this method will select incorrect interpretations. 
Z. Bounded search and ranked choice. Interpretations 
are generated by a bounded-effort search, each is 
assigned an individual quality .score of some sort, 
and the best is chosen. While this will not miss 
good but unexpected interpretations missed by 
first-find, it is wrong in at least two ways: a) it 
selects an interpretation (and discards others) when 
the quality difference between interpretations is 
insignificant, and b) it expends unnecessary 
resources making absolute quality Judgments 
where only relative Judgments are needed. These 
defects suggest an lmprovemenh 
3. Preeminence selection= perform a bounded-effort 
search for interpretations, and then select as beat 
the one (if any) having a certain threshold amount 
of demonstrable preferability over its competitors. 
The key to corre::t choice is determination that such 
a threshold difference in quality exists. DCS is 
designed to identify preeminent interpretations. 
Consider the information content in the fact that the 
best two interpretations have a quality difference exceeding 
a fixed threshold. This fact is sufficient to choose an 
interpretation, and yet it carries less information than is 
carried in a set of quality scores for the same set of 
interpretations. C~omputaUonal efficiencies are available 
because the work of creating the excess information can be 
avoided by proper design. 
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Given s tentative quality scoring of one's alternatives, 
several kinds of computations can be avoided. For the 
highest-ranked interpretation, it is pointless to perform 
computations whose only effect is to confirm or support the 
interpretation, (even thongh we expect that for correct 
interpretations the ways to show confirmation will be 
numerous), since these will only drive its score higher. 
For interpretations with inferior ranks, it is likewise 
pointless to perform computations that refute them 
(although we expect that refutations of poor interpretations 
will be numerous), since these will only drive their scores 
lower. Neither of these is relevant to demonstrating 
preeminence. 
Given effective controls, computation can concentrate 
on refuting good interpretation• and supporting weak ones. 
(Of" course, such computations will sometimes move 8 new 
interpretation into the role of highe•t-renked. They may 
also destroy an eppsrent preeminence.) If the gap in quality 
rating between the highest ranked interpretation end the 
next one rams/no significant, then proem/nonce has been 
demonstrated. 
Further efficlencles are possible provided that the 
maximum quality r•ting improvement front untr/ed support 
computation• can be predicted, since it is then posstblo to 
find case• for which the m•ximum support of • low-ranked 
interpretation would not eliminate an existing preeminence. 
Similar efficlencies can arise from predicting the max/mum 
loss 6f quality available from untr/ed refuter/one. This 
approach ls being implemented in DCS, 
IIL Control Structure -- • new AI programming 
environment called Hearsey-3 is being implemented at ISI for 
use in development of several systems. It is an augmentation 
and major revision of some of the control and data structure 
ideas found in He•rsey-ll \[Lesser & Erman 19773, but it is 
independent of the speech-understandlng task. Hecruy-3 
retains lnterprecess communicetion by means of global 
"blackboards," end it represents its process knowledge in 
many specialized "knowledge source" (KS) processes, which 
nominate themselves at appropriate t/rues bY looking at the 
blackboard, and then are opportunistically scheduled for 
execution. Blackbcerds are divided into "levels" that 
typically contain distinct kinds of state knowledge, the 
distinctions being ~jed as a gross filter on which future KS 
computation• ere considered. 
Hearsay-3 retsi,s the idea of a domain-knowledge 
blackboard (BB), and it adds a knowledge source scheduling 
blackboard (SBB) as well. Items on the SBB are opportunities 
to exercise particular scheduling speclslists celled 
Schedulln~ Knowledge Sources (SKS). 
The SBB Is •n ideal data structure For implementin~ 
Prominence scheduling. In DCS the SBB has four levels, 
called Refutation, Support, Evaluation and 
Ordinary-consequence. These correspond to a factoring of 
the domain K5 into four groups according to their effects. 
Knowledge sources in each of these groups nominata 
themselves onto a different level of the SBB. The 
scheduling-knowledge sources (SKS) perform preeminence 
scheduling (when a suitable range of alternatives ls 
available) by selecting available Refutation level 
opportunities for the highest-ranked interpretation and 
Support level opportunities for inferior ones. (The SBB and 
SKS Features of HearMy-3 •re only two of its many 
innovation•. ) 
The DCS B8 has 6 levels, named Text. Word-sense•, 
Syntax, Proposition•, Speech-acts •nd Goals. Goals and goal 
structures, which •re required in any successful analysis, 
only arise as explanations of speech acts. The KS used for 
deriving speech acts from utterances •re seperete from those 
deriving goals from speech acts. The hierarchic data 
structure representing an interpretation of •n utterance 
consists of units at vsrtou~ level• on the He•rsey-3 
blackboard. 
USING DCS 
These Innovations and sever•l others will be 
tested in DCS in •ttempts to comprehend human dialogue 
~athered from non-laboratory situ•tton•. (One of these L5 
Apollo astronaut to ground communication.) Transertpis of 
actual interpersonal dialogue• •re p•rtlcularly advantageous 
as study materiel, because they show the effects of ongoin~ 
communication •nd because they are free of the bieses and 
narrow view• inev/table in made-up example•. 
ACKNOWLEDGMENTS 
The work reported here was supported by NSF Grant 
MCS-70-07332. 
R EFER ENCES 
Lessor, V. R., and L. D. Ermsn, "A Retrospective View of the 
HEARSAY-II Architecture," Fl\[t~ Int~n~lovt~ Joint 
Con \[trtnct on Arti \[icl~ Intctlif~ct. Cambridge, MA, 
1977. 
Lenin, J. A., and J. A. Moore, "Dialogue Gamosz 
Meta-communication Structures for Natural Language 
Interaction," Coenitive Science. 1,4, 1978. 
Moore, J. A., J. A. Levin, •nd W. C. Mann, "A Goal-oriented 
Model of Human INalot~ue," flmerlcan Journal of 
Computational Lin£uistics. microfiche #67, 1977. 
Mann, W. C., "Dialogue Games," in MODELS OF pI4qLOGUE. 
K. Hlntlkka, st ~! (ads.) North Holland Press, 1979. 
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