Data Types in Computational Phonology

DATA TYPES IN COMPUTATIONAL PHONOLOGY Ewan Klein University of Edinburgh, Centre for Cognitive Science 2 Buccleuch Place, l~;dinl)urgh Ell8 91,W, Scotland Entail: klo in@od, ac. uk ABSTRACT This paper exanfines certain aspects of phono- logical structure from the viewpoint of ahstract data types, Our imnlediate goal is to find a for- mat for l)honological representation which will be reasonably f,'fithful to the concerns of theoreti: cal phonology while I)eing rigorous enough to a(I- rail a computational interl)retation. The longer term goal is to incorporate such representations into all appropriate general framework for llatn- ral language processing, i 1 Introduction One of the dominant paradignls ill cnrrell| coln- putat.ional linguistics is l)rovided by unification- based grammar formalisms. Such formalisms (of. IShieber 1986; Kasper t~ Rounds 1986)) describe hierarchic~d feature stl'tletllres, which iH inally ways would appear to be an ideal selling [br formal phonological analyses. 1,'eature bundles have long been used l)y phonologists, and more recent work on so-called feature geonletry (e.~. (Clements 1985; Sagey 19,~6)) has introduced hi- erarchy into such represenlations. Nevertheless. there are reasons to step back from standard feature-based apl~roaches, and instead to adopl the algebraic perspective of abstracl data types (AD'P) which has been widely adopted iu com- l)uter science. One general motivation, which we shall not e.xplore here. is thai Ihe aclivily of grantlnar writing, viewed as a process of pro- gramme specification, should be amenable Io sl~p- wise refinement in which the set of {sol neces- sarily isomorphic) n,odels admitted by a loose IThe work reported in this paper has [)¢:~,1, ~;tl ried ollt its part of the research i)rf)glitli/lll(!S o{ l]l(' ].{llnl&l[ (~oFiin/llllic&[iOll |lesea.rch (}(:Illl'C. sl/ppOl'led })3 the OK Economic and Social Rescalch (:ouncil aml the project Computational l)houoh)gy: .,I ('onst~aint-fh~s¢d Approach, funded by the IlV. ~qcience and Engineering I(t. search Council, under grant (;R/(;-22081. 1 am glalt'ful to Steven Bird. Kimba Newton and 'l'm/v Simou [m di> cussions relating to this work. AcrEs DE COLING-92, NAtc~S, 23-28 Ao~rr 1992 specilication is gradually narrowed down to a u,fiqtm 'algebra (cf. (Sannella & Tarleeki 1987) for an overview, and (Newton in prep.) for the apldication to grammar writing). A second mo- tivation, discussed in detail by (Beierle & Pletat 1988; Beierle K~ Pletat 1989; Beierle et al. 1988), is to use equational ADTS to provide a mathemat- ical foundation for h~ature structures. A third motivation, dominant in this pal)er , is to use the AI)T appl'oach lo provide a richer array of ex- plicit data types than are readily admitted by "p'tlre' feature structure approaches. Briefly, in their raw form, [eature terms (i.e., fnrnlalislns for describing h~alure stru(:tures) do not always pro- vide a perspicuous format for representing strllc- t II re. On the ADT approach, complex data types are built up from atomic types by means of con- structor functions. For example .... (where we use the underscore '_' to mark the position of the fimction's arguments) creates elements of type List. A dala type may also have selec- tor functions for taking …

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