scansion and analysis of prakrit verses by text...

Extrait de la Revue Informatique et Statistique dans les Sciences humaines XXIII, 1 à 4, 1987. C.I.P.L. - Université de Liège - Tous droits réservés.

Revue, Informatique et Statistique dans les Sciences humainesXXIII, 1-4, 1987, pp. 99-110

Scansion and Analysisof prakrit verses

by text-processing programs

C.M. MAYRIIOFER

The use of computers in the study of metre has sevcral attractions, aboyeaU the prospect of saving time and labour. There exist professional metricians,but for most students of language and literaturc, metre in Hs technical aspectsis a rebarbatiye subject, aU the more so far its dense and contradietorydocumentation. However, before one can use such deyices, one must be able tostate the rules of the metre in question. Now, even those who study literaturefor pleasure may be interested by the formalization of metrical rules, in so far asthe rules may be thought of as a model of the knowledge, the knowhow, whichin certain traditions of poetic composition is handed down from one generationto the next.

European literary scholars who have studied metrics as a pradical scienceare likely to have absorbed t.he rules for scanning classical Greek and Latinverse. In several projeets t.hese rules have been adapted to text-processingprograms and t.he results have appeared in a number of publications 1.

Unfortunately machines can make only an approximation of t.he scansionof a giyen line of verse, even if the approximation is right in as much as 95% 2

of cases. To improve this score their progl'ammers would haye to foUow thepath of reseal'ch into automatic translation, because the metrical propel'tiesof a text in classical Greek or Latin can he securely ascertained ouly artel' itsmeaning has been determined. In other words, the Greek and Latin alphabets

1 W. OTT, Melrische Analyse'l zur Ars Poetica des Horuz, Goppingen, 1970; S. HOCKEY,I. l\-IARRIOTT, Oxford Concordance Program, version 1.0 : user's manual, Oxford, 1980,rcpr. 1984, pp. 334-337; discussion and bibliography in C. I3UTLER, Computers in Linguistic,Oxford, 1985, p. 20.

2 OTT, p. 7


100 C.M. MAYRHOFER

do not sufficiently specify the phonetic properties of their respective languagesta permit accurate metrical analysis on the basis of the text alonc, whether byhumans or computers.

The case of another classical language \Vith a long tradition of metricalanalysis, Sanskrit, as \Vell as of its relations the Prakrits, is very different.The devanagari alphabet, in which these languages are usually writteu, hasabout twice as many characters as the Roman. This multiplicity of charadershears witness ta the precision of phonetic aoalysis in the Indian grammaticaltradition. It seems likell' that a preoccupation \Vith the accuracl' of orallyperformed ritual texts inspired the development ofthis highll' anall'tic alphabet,which has, thereforc, in principle, none of the ambiguities of the Grcck andRoman alphabets, and the fuies for scanning Sanskrit and Prakrit verses canbe translated into a text-processing program which will, again in principle,produce metrical analyses with 100 percent accuracy. This has been done, atleast for Prakrit 3.

The project to which l now turn concerns a particular Prakrit language.The Prakrits are regarded in the Indian tradition as the heirs of Sanskrit,the classical language par excellence. One of them, however, is qualified asapabhramsa, "decadencell

, being the furthest rernoved from the parent language.It is true that in sorne respects it is the nearest to the spoken languages of thefamily. Nevertheless in the evolution of literary styles in India it too becarne aclassicallanguage, and a substantial number of text.s in Apabhramsa, sorne ofthem very long, have been discovered and published, almost all of them duringthe course of this century 4. Still, it remains the runt of the family so far asscholarship is concerned. The tradition of linguistic and metrical commentaryis less secure than in the case of Sanskrit and of the other Prakrits, andmodern scholarship has not l'et settled the rules of the language. A generalproblern is that the editing of the texts is not sufficiently advanced to permit areliable sUl'vey of its features, and conversely, the absence of an authoritativephonology and grammar means that the editing of texts is hazardous. In orderto rnake progress in either direction, one must try to rnake progress in bothsimultaneously. The special interest of metre in Apabhramsa studies is thataIl known texts in the language are metrical. There is no Apabhramsa prose.Consequentll' one has the opportunitl' to benefit from the predictable featuresof verse to control the accuracy of an exemplar of a text, and by the saIlle tokenthe obligation to develop an adequate description of these features.

3 Dr. H. Nakatani of Tokyo University informed me in January 1985 thal he had the useof such a program.

4 References in S. LIENHARD, A llistory of Classical Poetry : Sans}';ri!·Pali·Prahit,Wiesbaden, 1984, index p. 290, S.v.


SCANSION AND ANALYSIS OF PRAKRIT VERSES 101

The first step is the conversion of the texts into machine-reaclable form,which process takes the form of typing them in transliteration uncler a programwhich provides line-references in a standard format. For the transliterationwhieh involves rendering the 38 or so characters used in Apabhramsa by the26 of the Roman alphabet, certain deeisions had to be taken and adhered to.1 deeided to use the established system, in partieular the representation ofaspirate consonants by digraphs (e.g. "Kh"), except that instead of a variety ofdiacriticai marks (points above and below the letters, microns and macrons) 1use majuscules for most marked letters and random characters for one or two. Itwould have greatly simplified the programs described below if 1 had avoided thedigraphs, firstly because they constitute a peculiar set of characters, secondlybecause "h" in the usuaI system, and in mine, has an independent existenceas a let ter j but to keep to convention seemed preferable mnemonically. Thebest system for this purpose is the one which causes the least hesitation in theoperator who is converting and typing simultaneousIy.

Although such work ideally demands no refiection on the operator'spart, it represents a significant stage in metrical analysis because, despiteits multiplieity of letters, the devanagari alphabet is not perfectly suited toApabhramsa. Many of the letters are never used, except when an older Prakritor Sanskrit itself is quoted j sorne letters are used interchangeably; sorne sounclsare not represented by any standard letter. Two cletails will suffice to describethe significance of this for metrical analysis, but first sorne terms will have tobe defined. The metrical basis of Apabhramsa verse is quantitative, that is,the recurring elements of the system are classified by duration, not stress orauy other linguistic feature. The fundamental element is the syllable, which 1shaH not attempt to define here except to note that its essential constituent isa vowel. For metrical purposes what matters is that a syllable may be either"long" or llshort". Vowels too are classifled as Ulong" or "short". Any syllablewhich contains a long vowel is long j a syllable containing a short vowel may beshort or, if a group of two consonants follows the vowel, long. Now, the vowelsin Sanskrit transcrihed as Ile" and ClO" are regarded as diphthongs and hencehy clefinition long. In the Prakrit languages, however, there exist both long andshort "e" and "0" vowels. The majority of examples occur hefore a group oftwo consonants, indeed they are conditioned by that envÎronment 5. Hence theexistence of these short vowels is of no metrical significance. But they can occurin other contexts as weil, they can he metrically short, and the alphabet has

oS The so-called law of two morae : W. GEIGER Pali Literatur und Sprache, Strasbourg,1961, p. 42. The rule that a short vowel becomes long if followed by a double consonantis enunciated by the Indian grammarian Hemacandra (1088-1172 AD)j see R. PISCHEL,Grammatik der Pral.:rit·Sprachen, Strasbourg, 1900, repr. Hildesheim, 1973, pp. 72-3.


102 C.M. MAYRHOFER

no way of distinguishing them from the long vowels "e" and "0". Secondly, thePrakrits have two kinds of nasalization of vowels which have different metricalvalucs 6• In written and printed texts these sounds are represented sometimes bytwo different signs, sometimes by one and the same. Clearly, if the texts are tohe transliterated, as they must he for computer processing, the transliterationshould he explicit and consistent with regard to these matters. And when onemakes a choice of this kind one is adding information to the text, in effedperforming the first step in scansion.

The scanning program itself is a homespun affair with no pretentions toelegance or security. lt would no doubt have both these quaHties if 1 had used theservices of a professional programmer, but unless one is lucky enough to have atone's disposaI a programmer interested in literary problems, it is probably easierto learn the rudiments of a suitable language (in this case SIMULA) and do itoneself. Briefiy, the program takes as input a file in a standard format in whicheach line represents a line of verse j by a series of conditions it translates eachline into characters of three types standing respeetively for short syllable, longsyllable and word-division; this string is read into an array. The array is passedto a procedure which converts each grade into one of three symbols, which havea rough resemblance to the symbols of micron (HU"), macron ('1_") and caesura«( l'') as used in European metrical scholarship. The array is then output as alîne. The most complicated part is the translation from alphabet into metricaltypes, which needs to he sensitive to a context that in different cases can includethe character before, the character after 1 and up to two characters following aword division after, the character under consideration. The output Hne consistsof a reference to the line of text, an integer representing the metrical lengthof the line in terms of short-syllable equivalents, and the line as scanned. Theinteger is used for sorting a corpus of scanned Hnes into blocks of related lines J

the metres being traditionally classified by the length of the Hne.

The symbols used could easily he replaced by others, for example ":" and"Sil in imitation of the symbols sometimes used in works by Indian scholars.More crucial than their shape is the nUInber of columns that they occupy j thelong-syllable symbol occupies four, the short-syllable symbol two, with in eithercase the rightmost column being a blank space for the word-division symbol,which when it occurs does not occupy a column of its owu but fits iuto theother symbols. In this way, as the Hne is read from left to right, the number ofcolumns traversed bears an exact relationship to the metricallength of the Hileat that point.

6 PISCIIEL, pp. 131-2. '



The purpose of this is to make it possible to examine a listing visually andquickly pick up any irregularities. Though not l'very fault in the text will l'l'suitin an irregular scansion, it is almost certain that any irregularity in scansionwill be caused by a fault in the text, introduced at sorne stage in the copyingprocess from writer to printer to computer file. Flirther, since as we have seenthe transliterated text carries more information than the original, sorne errorswill be located in this information. Finally it is possible that the program maynot he capable of correctly handling a particular cornbination of charaeters,though by now aIter rnany adjustments to eliminate banal inadequacies anynew failures will add significantly to what is known about the language. Hence,once a text has been typed in transliteration, it is very useful to print out thescansion of the file and have it by one's side while collating the transliteration.

In Apabhramsa texts a particulaI' metre may be used throughout a blackof verses, after which comes another block of a different metre, or a recurringstrophe-like arrangement composed of verses of different length may be used, orthe verses may be mixed. Espccially in the last two cases it is useful to sort thefile of scanned verses by the integer representing the metrical length of eachline. This then produces blocks of related verses, which again are useful forvisual checks. The correctly-scanning Hnes will be grouped together by metre,and any verses which contain a metrical fault that influences their length willfall outside the black. Often there will occor between one black of regular linesand the next a well-defined group of stragglers that need editorial attention.

In such a listing the eye will pick UP, not only irregularities, but alsoregularities. A particular metre is defined, not only by its length in shortsyllable equivalents, but also in terms of perrnitted sequences of long and shortsyllables. In a black of related lines the compulsory, preferred and forbiddensequences form visible patterns, and by means of such an examination it ispossible to check the traditional rules and to suspect further rules not specifiedby the tradition. There is no doubt a circularity in using the rules of scansion tocorrect a text and at the same time using the text. to deduce rules of scansion,but such a praetice is inherent in the process of editing a text.

When finally the whole file scans regularly, one can proceed ta use thescanned file, the output of the first stage, as input for a further stage, that ofsubmitting the traditional rules and one's own intuitions concerning the natureof a given metre to a rigorous analysis. There are two fundamental approachesto metrical analysis at this level, sometimes qualified as "outer" and "inner"metrics : bath study permitted sequences of long and short syllables, but theformer concentrates on the verse and its articulations, the latter concentrateson the word in relation to the verse and its articulations. Thus for example inthe Greek and Latin hexameter, the verse must begin with a long syllable (-);


104 C.M. MAYRHOFER

that advances the count of short-syllable equivalents ta 2; the count may thenjump ta 4 with another long syllable (- -), or it may increase fust ta 3 (_ V)then ta 4 (- VV) with short syllables, but it must then advance from 4 ta 6 :- - - or - y v _ the count can never he 5. Then follows one long syllable or twoshort and sa on, ta the line limit of 24. The regtÙar increment in the Hoe of 4short-syllable equivalents, consisting of one long syllable followed by a long ortwo shorts, constitutes a foot. Indian paeties also uses the ward equivalent ta(({oot H

) but in a different sense. The ward gana is used with reference ta Prakritverse for a concept somewhat like that of the foot, except that not every ganain a verse has the same valuc, 80 that the formula of a verse might bel Însteadof for example 6 * 4 as in the Greek and Latin hexameter, something likc6+4 +3+6+4 +1 , and the specifications for a particular gana can range from"only this sequence of long and short syllables is allowedll ta l'any combinationof long and short syllables is allowed provided that the total of the short-syllableequivalents is n" 7.

The program which deals with the "outer metric1J of Apabhramsa versebegins by collecting certain data interactively from the terminal : the nameof the metre (for the heading), the number of gana. in a verse, the number ofshort-syllable equivalents in each gana. The SUffi of these is used to select versesin the file for closer attention j the program then asks the user to prescribe twofeatures of the verse in the form of two columns of the scanned file (e.g. incolumn 21 and column 25 the charader Il U" must appear) so that differentmetres of the same length can be distinguished. After the data are elicited, theprogram reads the scansion file Hne by Hne, checks each Hne for its metricallength, and if the length is that of the verses under investigation, applies thecolumn-matching test. If the liue passes the test , the program splits it into ganasas prescribed. Each gana is matched against an array in which are accumulatedthe gana-types found during the current run, and a two-dimensioned integerarray keeps count of the occurrences of each type in each place of the verse. Theresults are tabulated with the actually-occuring gana-types, sorted by length,along one axis and a heading identifying the gana by its place in the line alongthe other j the intersections give the number of times that the gana takes aparticular form at a particular place. See table 1 for an example of the outputof this program j the verses analysed are from the 8th chapter of SiricandaKahako3a.

7 For a view of the basis and development of gana metres, see E.I<. WARDER, PailMetre : a contribution to the hi3tory of Indiar~ Literature, London, 1967, chapter vi.There are important collections of data in C. CAPPfil,l,ER, Die GanachandM, Leipzig, 1872,repr. in Kleine Schriften, cd. S. LIENHARD, Wiesbaden, 1977, pp. 35·156j L. ALSDORF,Apabhram3a.dudien, Leipzig, 1937, repr. Nendeln, 1966; H. BHAYANI, The Samdesa rasakaof Abdul Rahman... , Bombay, 1945.



TABLE 1: GANA TYPES

Number of doha read in scande: 40GANAul 0 0 0 0 0 40u u Ul 0 0 25 0 0 0ulu Ul 0 0 13 0 0 0U U U 0 0 2 0 0 0u Ul__ 0 Il 0 0 6 0ulu _ 0 2 0 0 15 0__ U U 0 1 0 0 0 0---- 0 7 0 0 7 0__lU u 0 3 0 0 0 0U u __ 0 4 0 0 12 0u UIU Ul 0 1 0 0 0 0U U U U 0 3 0 0 0 0

-1- 0 3 0 0 0 0U U u ul 0 1 0 0 0 0u UIU u 0 3 0 0 0 0U __ U 0 1 0 0 0 0u ulu u __ 1 0 0 1 0 0UUluUluu 0 0 0 1 0 0u Ul__ u Ul 1 0 0 0 0 0u Ul____ 2 0 0 1 0 0U u __lu Ul 1 0 0 0 0 0uuuluuUI 0 0 0 1 0 0u UI__I_ 1 0 0 1 0 0__ UIU __ 2 0 0 1 0 0__ uu __ 2 0 0 0 0 0U U ____ 0 0 0 1 0 0------ 2 0 0 0 0 0__ UIUlu u 1 0 0 0 0 0__ u Ul_ 4 0 0 6 0 0UUluuuUI 0 0 0 1 0 0UUluuUU 0 0 0 1 0 0____ u u 1 0 0 3 0 0__ u U-I 1 0 0 0 0 0__ u __ Ul 0 0 0 1 0 0--I-_U Ul 3 0 0 2 0 0

--lU U U U 0 0 0 2 0 0uuuuluul 1 0 0 1 0 0u ulu ul__ 1 0 0 3 0 0__ uuluul 0 0 0 1 0 0u u ____1 0 0 0 1 0 0__ ulul_ 1 0 0 1 0 0____ u ul 1 0 0 1 0 0uuuuluu 1 0 0 0 0 0UUUIU __ 2 0 0 1 0 0u u u __ u 1 0 0 0 0 0__ U __ u 0 0 0 1 0 0(...)

"Innee' metrÎc can not he entirely separated from <Iouter". It Îs clear that


106 C.hL MAYRHOFER

the permitted sequence of long and short syllables in a verse determines theshapes of words that are admissible in that verse at particular places in theverse. But Hinnee' metric is alsa concerned with, ta put it one way, the metricallength of words occurring in a verse, to put it another \Vay, \Vith the places ina verse where one word may end and another begin. Concerning the former,there are regularities ta he discovered in the favoured word-shapcs of a givenlength, bath absolutely and in relation \Vith their place in the verse; traditionalmetrics has nothing ta say about these. Concerning the latter, traditionalmetrics prescribes places in the verse where there is always a word-division,but is reticent about the places where there is never a word-division. This isnot the place to give details of the phenomena to bc investigated; the methodof the program which tabulates them is, briefly : for a line of given metricallength, which passes the colunm-content test as abovc, read the metrical shapesbetween word-divisions and store them in a text anay of which each gradecontains one type, with a count being kept in a two-dimensioned integer arrayof the occurrences of each type in a particular place. The results are thentabulated with the actually-occurring ward-types, sOl'ted by length, along oneaxis, and along the other axis a heading which divides the Hne into columusnumbered to represent the place in the verse, 50 as to locate the places wherethe words begin j the intersections give the number of times that a word of aparticular shape begins at a particular place in the line. Ta facilitate the stndyof the general metrical nature of the text, the SUlU of aU the occurrences of aword of a particulaI' shape is given at the end of a row. One cau then see at aglance if, for example, anapaestic words are favoured over dactylic, or whatever.Ta facilitate the study of the obligatory and fOl'bidden ward-divisions, the lastrow gives the sum of eaeh column. Table 2 gives an example of the output ofthis program, using the same material as in table 1.

The aim of these programs is essential1y to reconstruct the criteria ofcorrectness in the various metres of Apabhramsa verse, or to verify the criteriain cases where they are provided by traditional eommentaries or have alreadybeen estabHshed by modern scholarship. It seems entirely appropriate to use acomputer ta perform quickly and accurately the inherently disagreeable tasksof gathering and sorting the data, as a means to the end of deducing the rulesby which the poets worked, sa ta speak. 1 pass over the problem of the statnsof these rules. There is probably no way of deciding whether the regularitieswhich emerge from this presentation of the data arise from the system of thelanguage itself or from the craft of the poet working within a tradition; mostcases would no doubt involve a mixture of the two in varying proportions. lhave resisted the temptation to explore the regularities for themselves beyondthe point where the)' may intuitively be associated with or considered as modelsfor the practice of the poets. But that there are perspectives in the formai basis


SCANSION AND ANALYSIS OF PRAKRIT VERSES

TABLE 2 : WORD TYPESNumber of 24-morae lines read in scande: 40

LiST OF WORD TYPES

107

1 :2:3 :4:5:6:7:8:9:

10:11:12 :(... )37 :38 :39 :40 :41 :42 :43 :44 :

uu u

u u u__ UU __ U__ UUU U __

U U U U

__ uuu____ U

______ u u uUUU __ UUUUU UUUU U U U __ U__ U U __ U U __ U____ U U __ U U U

UUUU __ UUUUUUU __ UUU U U __ U U U U U U U U __ U __ U U U __ U

of versification beyond this point is constantly impressed on one. To take oneexample : in a rhyming couplet in the paddhadika metre there are 32 short·syllable equivalents, and an obligatory word-break for the rhyme at the midpoint. Hence the longest possible word contains 16 short-syllable equivalents,and words of this length lli'e not uncommon. In this poetic language there is nosimple inverse relationship hetween word-length and frequency. The number ofpossible shapes of words hetween 1 and 16 short-syBable equivalents is about4000. Sorne of these are excluded by the metre, but probably, the metre beingvery accomodating, less than half : say then that the number of possible shapesis 2000. In praetice about 100 seems ta he the maximum, and it is a practicalmatter for the programmer because it influences the dimensioning of the arrays.To explain why relatively few of t,he possible word-shapes are used one wouldprobably have to invoke the formai properties of the language itself.

A further use for a file of scanned verses is the study of rhyme. As it happens, not ouly are aIl known Apabhramsa texts in verse but also nearly aIl


108 C.l....I. MAYRHOFER

the verses are rhymed. Traditional pocties recognizes rhyme or rather rhymelike phenomena as a repetition of sounds at the end of \Vords or homonymous\Vords at the verse end. This leaves l'oom for further investigation in terms ofthe lexical choice, morphology and metrical shape of rhyming clements. To begin with, it is necessary ta define rhyme, as understood in European pocties,in terms of metre. Words with similar cudings are ouly rhymes if they Dccur ata determined place in a verse: typically, the end of the verse, but that faisesthe question of the relationship between the verse and the lines as presentedon the page. For example the verse referred to above can he printed as

(1) (16)

(17) (32)

or as

(1) (32)

In the former case, each Jiue will end with a rhyming word; in the latter,there will be a compulsory word-break after the 16th place, and the word wruehends there will rhyme with the word at the end of the line. A more eomplicatedexample is shown in the figure below, in which the numbers l'epresent the placein the verse, the letters represent the words which rhyme \Vith one another inthe same or in successive lines :

(1) (lO)a (18)a (31)b

(1) (lO)e (18)e (31)b

It would undoubtedly have simplified the programming if the verses weretyped so that rhymes occurred only at the end of lines, but for the sake of easein collation and cross-reference the lines represent the verses as they are usuallyprinted. So the program must n.nd the places in the verse where a rhyming wordi8 to be expeeted, and extraet that word. This is done by reading the text fileand the scanned file concurrently (the latter, being derived from the former,corresponds with it line by Hne) and counting in any particular Hue, startingat the end of the Hne, the number of word~divisionmarkers that occur in thescaIUled text before the prescribed metrieal place is reached (this is of course1 in the most frequent and trivial case, end-rhymes); then extracting the wardfrom the text which occurs after the same number of word-divisions, againcounting from the right. The same process is repeated as necessary in arder taextraet the other member of the rhyming pair, and once that has been done,



the elements that are common to the ends of both words are extraeted. This issimple enough when both occur on the same line, a little more delicate whenthey OCCUl' on different lines, and qui te awkward when there is a mixture ofthe two schemes as in the example above. In praetice 1 have a procedure forthe case of rhymes in the same line and another for the case of rhymes in adifferent Hne and 1 simply rewrite a section of the prograrn to cope with eachparticular job. Tt would be more elegant, but very time- consuming, to writea prograrn that could accommodate every pattern. When the rhyming wordshave been extracted, the program sends to a file a record consisting of theelements cornmon to the endings of the two words, - in other \Vords the rhyme,- reversed for sorting purposes, and the two words involved, together with theHne reference of one of them.

Of these higher-Ievel programs, the least useful, in the sense of givingnew insights, is the most obvious, that which classifies gana. Scholars havecollected this kind of material before, and it is at least reassuring to findthat the results produced by my program correspond with those producedmanualiy by others. If such statistics are needed again, they may be entrustedto a machine. The rhyme program was written and applied in the hope ofconfirrning a hypothesis that, not evcry allowable and actually-occurring wordending is used in rhyme, but that a relatively smali group of rhyming elementsis used relatively frequently. It did not fulfil trus hope. There are matters tobe discovered about the choice of rhyrning words, but the phenornenon is notsimply lexical or morphologieal as was first thought. On the other hand thesorted output of rhyming words revealed at the head of the list an unexpectedgroup of blanks, where the words in rhyming position did not end with commonclements. More preeisely, the common elements were of a kind that the programwas not written to deteet. Such rhymes are of considerable interest for the studynot only of the poetics but also of the phonemics of the language: it appearsthat the poetic rules deem certain non-identicalletters to correspond with oneanother and certain non-nun letters to he nul!. These rules are of course notdirect evidence for the phonemics of the language but they clearly need tobe taken into account under that heading 8• The rhymes can perfeetly weIl hecollected manually. However when one is not sure at the outset what one islooking for, it is aIl advantage to be able to repeat the process of collectionwith different criteria in negligible time, and this can be done by means ofminor modifications to the program.

8 For discussions of "impure" rhymes see H. JACOBI, Bhavüatta Kaha von Dhanavala :eine Jaina Legende in Apabhromsa, Munich, 1918, pp. 52-3; G. BAUMANN, Drei Jainagedichtein Alt·Gujarati, Wiesbaden) 1975, pp. 19·21.


110 C.M. MAYRHOFER

The most useful program is without doubt the one which classifies word-types. Not ouly does it yield interesting information on the structure of theverses which are submiUed ta it, but it also provides a table of the frequencyof occurrence of caeh metrical shape of the words in a text. Inasmuch as me-trieal shape is considered to be a factor in the historieal morphology of theludo-Aryan languages 9 , this material has an importance beyond the study ofpoetic practices, and in a subsequent project this funetion of the program willbe applied ta the automatic construction of word-lists arranged by metricalshape from the texts uncler consideration.

TABLE OF DISTRIBUTION OF WORDTYPESBY STARTING POINT

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41... SUM

1 o 0 o 3 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 52 8 0 2 0 3 0 2 0 1 0 0 13 o 11 0 5 0 2 0 3 0 503 6 0 3 0 1 0 4 0 0 0 0 0 0 5 0 2 0 0 0 0 0 214 3 0 o 0 0 0 0 0 3 0 2 0 0 2 0 0 2 1 0 0 0 135 4 0 1 0 0 0 0 0 4 0 0 0 0 3 0 0 0 9 0 0 0 276 o 0 o 1 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 o 15 187 5 0 4 0 4 0 0 0 0 0 0 0 0 6 0 2 0 0 0 0 0 218 1 0 o 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19 1 0 o 0 1 0 1 0 0 0 0 0 0 2 0 1 0 0 0 0 0 6

10 o 0 o 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 111 o 0 o 0 0 0 0 o 10 0 0 0 0 0 0 0 0 0 0 0 0 1012 o 0 1 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 5 0 8( ...)37 o 0 o 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 138 o 0 o 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 139 o 0 o 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 140 o 0 o 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 141 1 0 o 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 142 o 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 143 1 0 o 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 144 1 0 o 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

SUM 40 0 14 7 15 1 13 2 21 0 2 13 o 38 o 16 5 17 0 12 15

9 O. VON HINÜBER , Das iiltere Mittelindisch im überblick, Vienna, 1986, p. 90.

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