<?xml version="1.0" standalone="yes"?>
<Paper uid="C94-2161">
  <Title>Anytime Algorithms fl)r Speech Parsing?*</Title>
  <Section position="5" start_page="997" end_page="999" type="metho">
    <SectionTitle>
3 Breadth and Depth of Analy-
</SectionTitle>
    <Paragraph position="0"> sis In the following we will ask whether and how the idea of anytime producers can be applied within the active chart parsing algorithm scheme with feature unification. Although the analogy to decision making in planning where the idea of anytime algorithms has been developed seems to be rather shallow, we can, for the operation of the parser, distinguish between depth and breadth of analysis 7.</Paragraph>
    <Paragraph position="1"> We define depth of analysis as the concept refering to the growing size of information content in a feature structure over a given set of non-competing word hypotheses in a certain time segment during its computation. Larger depth corresponds to a more detailed linguistic description of the same objects.</Paragraph>
    <Paragraph position="2"> In contrast, we understand by breadth of analysis the consideration of linguistic descriptions resulting from the analysis of growing sets of word hypotheses, either from growing segments of the utterance to be parsed or from a larger number of competing word hypotheses in a given time segment. null q'o regard breadth of analysis as a measure in the context of the anytime algorithm concept is in a sense r not to |)e confused with depth-first or breadth-first search.  trivial: Considering only one l)arse, the more processing time the parser is given the larger the analyzed segment of the input utterance will be. In general, larger breadth corresponds to more information about competing word hypotheses in an (half-) open time interval as opposed to more information about a given word sequence. So, obviously, breadth of analysis does not correspond to what is intended by the concel)t of anytime algorithms, whereas depth of analysis meets the inliention.</Paragraph>
    <Paragraph position="3"> If an utterance is syntactically ambiguous, we (:an compute more parses the more processing time the parser is given. Therefore, tohis case is apart, icular instance of depth of analysis, beeaase the same word sequence is considered, and not of breadth of analysis given the definition above. In this case one would like to get the best analysis in terms of the quality scores of its constituents first, and other readings late,', ordered by score. If the parser works incrementally, what happens to be the case for the Verbmobil/15 parser s, the intended effect car, be achieved by the adjustment of a strategy parameter namely to report the analysis of a grammatical fragment of the input utterance as soon as it is found.</Paragraph>
    <Paragraph position="4"> At least one distinction might be useful for the Verbmobil/\[5 parser. In our parser a category check is performed on two chart edges for eIficiency reasons, and only if this check is successflfi, the unificatkm of the associated feature structures is performed, llence, an interrupt would be admissible after ,,he category check. In this case we emphasize a factorization of the set; of constraints in two distinct subsets: phrasal constraints which are processed by the act.iw~ chart parsing algorithm schema (with l)olynomial complexity), and functional constraints which are solved by the unification algorithm (with exponential complexity). 'rhe interface between both types of constraints is a crucial place for the introduction of control in the parsing process in general 9 Since we use a constraint-hased grammar formalism, whose central operation is the unification of feature structures, it does not make sense to admit inter rupts at any time. Instead, the operation of the parser consists of a sequence of transactions. At the most coarse grained level, a transaction would be an application of the flmdamental rule of active chart t)arsing, i.e. a series of operations which ends when a new edge is introduced into the chart, including the computation of the feature structure associated with it. Of course this argument holds when an application of the fundamental rule results in another application of it on subunits due to the reeursive structure of the grammar ruleQ deg. Certainly one might ask whether a smaller grain size makes sense, i.e. the construclion of a feature structure should itself he interruptible. In this case one could think of the possibility of au interrupt. Sand for Gul,t' as well 9 cf. \[Maxwell and Kaplan 1994\] ldegThis h,'ts been implemented in the interrupt system of (lul,l) \[Ggrz 1988\].</Paragraph>
    <Paragraph position="5"> after one feature in one of the two feature structures to be unified has been l)roeessed. We think that this possibility shouhl be rejected, since feature structures usually contain eoreli'.rences. If we consider a partial feature structure - - as in an intermediate step in the unitication of two feature structures in the situation where just one feature has been processed, this structure might not be a realistic partial description of the part of speech under consideration, but simply inadequate as long as not all embedded eoreferences have been established. It seems obvious that the grain size cannot be meaningfully decreased below the processing of one feature. Therefore we decided that transactions must be defined in terms of computations of whole feature structures.</Paragraph>
    <Paragraph position="6"> Nevertheless, a possibility for interrupting the computation of a feature structure could be considered in case the set of featnre, s is divided in ~wo classes: features which are obligatory and features which are optional. Members of the last group are candidates for constraint relaxation which seems to be relevant with respect to robustness at least in the case of speech parsing. We have just started to work on the constraint relaxation problem, but there is no doubt that this is an important issue for further research. Nevertheless, at the time being we doubt whether the above mentione.d problem with coreferences couht be avoided in this case.</Paragraph>
    <Paragraph position="7"> A further opportunity for interrupts comes up in cases where the processing of alternatives in unifying disjm)ctiw~' feature structures is delayed. In this case, unilication with one of the disjuncts can be considered as a transaction.</Paragraph>
    <Paragraph position="8"> Another chance R)r the implementation of anytime behavior in parsing arises if we consider the grammar from a linguistic perspective ~ oppose.d to the purely formal view taken above. Since semantic construction is done by our grammar as well, the functional constraints contain a distinct subset for the purpose of semantic construction. In a separate b, vestigation \[Fischer 1994\] implemented a version of A-I)t{;I ~ \[l)inkal 1993\] within the. same feature unification fo&gt; realism which buihts semantic structures within the framework of Discourse Representation Theory. It has been shown that the process of DRS construction can be split in two types of transactions, one which can be performed incrementally basically the construction of event representations without temporal information -- and another one which cannot be concluded before the end of an utterance has been reached - - supplying temporal information. Since the first kind of transactions represents meaningfnl partial semantic analyses those can be supplied immediately on demand under au anytime regime.</Paragraph>
    <Paragraph position="9"> The possibility to process interrupts with the restriction that the currently active transaction has to be complete.d in advance has been built into the Verhmobil/15 parser, using the APC protocol (of. Appendix). It therefore exhibits a limited anytime behavior.</Paragraph>
  </Section>
  <Section position="6" start_page="999" end_page="999" type="metho">
    <SectionTitle>
4 Feature Unification as an
</SectionTitle>
    <Paragraph position="0"/>
    <Section position="1" start_page="999" end_page="999" type="sub_section">
      <SectionTitle>
Anytime Algorithm?
</SectionTitle>
      <Paragraph position="0"> Up to now, in our discussion of an appropriate grain size for the unification of feature structures we consid: ered two cases: the unification of two whole feature structures or the unification of parts of two feature structures on the level of disjuncts or individual features..In all of these cases unitication is considered as a single step, neglecting its real cost, i.e. time constraints would only affect the number of unification steps, but not the execution of a particular unification operation.</Paragraph>
      <Paragraph position="1"> Alternatively, one might consider the unification algorithm itself as an anytime algorithm with a property which one might call &amp;quot;shallow unification&amp;quot;. A shallow unification process would quickly come up with a first, incomplete and only partially correct solution which then, given more computation time, would have to be refined and possibly revised. It seems that this prop-erty cannot be achieved by a modification of existing unification algorithms, but would require a radically different approach. A prerequisite for that would be a sort of quality measure 11 tbr different partial feature structures describing a given linguistic object which is distinct from the subsumption relation. To our knowledge, the definition of such a measure is an open re: search question.</Paragraph>
    </Section>
  </Section>
class="xml-element"></Paper>