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Computers and the Humanities 23:105--111, 1989. © 1989 KluwerAcademic Publishers. Printed in the Netherlands. Two Relational Databases for Finding Text Paraphrases in Musicological Research John Walter Hill and Tom R. Ward School of Music, University of Illinois at Urbana-Champaign, 2136 Music Building, 1114 West Nevada Street, Urbana, IL 61801, U.S.A. Abstract: In order to locate text paraphrase in Vivaldi's opera librettos, as a clue to the composer's reuse of his own arias in operas for which the music is lost, and in order to reconstruct a pattern of interdependency among a group of related medieval music treatises, the authors created their own rela- tional databases using the Savvy-PC programming language. The crucial, unique feature of this language is a COMPARE Tom Ward (Ph.D., Musicology, University of Pitts- burgh) is currently associate professor of Music and Coordinator of Graduate Studies in Music at the University of Illinois at Urbana-Champaign. He is the author of The Polyphonic Office Hymn from 1400 to 1520 (Stuttgart, 1980), collaborated in the production of the Census-Catalogue of Manu- script Sources of Polyphonic Music (Stuttgart, 1979--1988) and has contributed articles and reviews to many journals. Current research inter- ests include music and musicians in central Europe during the fifteenth century and the place of music in late medieval universities in addition to the databases described in this issue. John Hill (Ph.D., Musicology, Harvard University) is professor of Music at the University of Illinois. He is the author of The Life and Works of Francesco Maria Veracini (Ann Arbor." UMI Research Press, 1979), Vivaldi's Ottone in villa: A Study in Musical Drama, Drammaturgia musicale veneta, 1 (Venice: Fondazione Giorgio Cini, 1983), and of numerous articles. From 1983 to 1986 he served as Editor-in-Chief of the Journal of the American Musicological Society. He is currently writing a book on the musical patronage of Cardinal Montalto in the early seventeenth century. command that transcends the limitations of Key Word in Context searches. This system puts the scholar in control of programming functions on all DOS microcomputers, and outputs universally transferrable ASCII data files. Key Words: music, opera, libretto, Vivaldi, musicology, Savvy-PC, paraphrase, concordance. The objectives, requirements, limitations, and experience of the present authors are probably shared by many readers. The authors each needed to search through a large quantity of text in order to find instances of paraphrasing, for different purposes: in one case to infer from text parody the presence of reused arias in operas whose music has been lost, and in the other case to establish a pattern of interdependence among related late- medieval music treatises. As a practical matter, we wanted the databases to be portable to the largest number of computers that we or our colleagues would be using in the future. We wanted to ensure the straightforward exchange of data between all computers, leaving the precise form and format of the data as open as possible. Although neither of us are computer experts, we created and managed our own program and data environment, because we found that a creative interaction between understanding of subject matter and the creation and revision of programs was fundamental to our progress and good results. The two kinds of knowledge operated on each other. We selected a relatively little-known relational database programming language called Savvy PC, marketed by Excalibur Technologies Corporation, which runs on any MS-DOS microcomputer. 1 We chose this in preference to better-known software

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Page 1: Two relational databases for finding text paraphrases in musicological research

Computers and the Humanities 23:105--111, 1989. © 1989 KluwerAcademic Publishers. Printed in the Netherlands.

Two Relational Databases for Finding Text Paraphrases in Musicological Research

J o h n W a l t e r Hil l and T o m R. W a r d

School of Music, University of Illinois at Urbana-Champaign, 2136 Music Building, 1114 West Nevada Street, Urbana, IL 61801, U.S.A.

Abstract: In order to locate text paraphrase in Vivaldi's opera librettos, as a clue to the composer's reuse of his own arias in operas for which the music is lost, and in order to reconstruct a pattern of interdependency among a group of related medieval music treatises, the authors created their own rela- tional databases using the Savvy-PC programming language. The crucial, unique feature of this language is a COMPARE

Tom Ward (Ph.D., Musicology, University of Pitts- burgh) is currently associate professor of Music and Coordinator of Graduate Studies in Music at the University of Illinois at Urbana-Champaign. He is the author of The Polyphonic Office Hymn from 1400 to 1520 (Stuttgart, 1980), collaborated in the production of the Census-Catalogue of Manu- script Sources of Polyphonic Music (Stuttgart, 1979--1988) and has contributed articles and reviews to many journals. Current research inter- ests include music and musicians in central Europe during the fifteenth century and the place of music in late medieval universities in addition to the databases described in this issue.

John Hill (Ph.D., Musicology, Harvard University) is professor of Music at the University of Illinois. He is the author of The Life and Works of Francesco Maria Veracini (Ann Arbor." UMI Research Press, 1979), Vivaldi's Ottone in villa: A Study in Musical Drama, Drammaturgia musicale veneta, 1 (Venice: Fondazione Giorgio Cini, 1983), and of numerous articles. From 1983 to 1986 he served as Editor-in-Chief of the Journal of the American Musicological Society. He is currently writing a book on the musical patronage of Cardinal Montalto in the early seventeenth century.

command that transcends the limitations of Key Word in Context searches. This system puts the scholar in control of programming functions on all DOS microcomputers, and outputs universally transferrable ASCII data files.

Key Words: music, opera, libretto, Vivaldi, musicology, Savvy-PC, paraphrase, concordance.

The objectives, requirements, limitations, and experience of the present authors are probably shared by many readers. The authors each needed to search through a large quantity of text in order to find instances of paraphrasing, for different purposes: in one case to infer from text parody the presence of reused arias in operas whose music has been lost, and in the other case to establish a pattern of interdependence among related late- medieval music treatises. As a practical matter, we wanted the databases to be portable to the largest number of computers that we or our colleagues would be using in the future. We wanted to ensure the straightforward exchange of data between all computers, leaving the precise form and format of the data as open as possible. Although neither of us are computer experts, we created and managed our own program and data environment, because we found that a creative interaction between understanding of subject matter and the creation and revision of programs was fundamental to our progress and good results. The two kinds of knowledge operated on each other.

We selected a relatively little-known relational database programming language called Savvy PC, marketed by Excalibur Technologies Corporation, which runs on any MS-DOS microcomputer. 1 We chose this in preference to better-known software

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106 J O H N W A L T E R H I L L A N D T O M R. W A R D

because of the unique "COMPARE" command that is part of the Savvy PC programming lan- guage. Imbedded in a loop, COMPARE will automatically match the complete text of an aria or a sentence of a treause with every other aria text or sentence in every record of every file in the database -- it will compare them letter by letter, not merely word by word. Beginning with the first letter of the matrix text, the program finds the first instance of that letter in the comparison text. Once this match is found, it proceeds to the next letter of each text. If these letters match, then the third letters are compared. As soon as the string of letters in the comparison text yields a mismatch, the program searches for the next match to the first letter of the matrix text. After finding all string matches that begin with the first letter, the program proceeds to the second letter of the matrix text, and so on to the end. All the while, the COMPARE function keeps track of the number and length of the string matches by calculating a number (the "score") to represent the degree of similarity between each pair of texts compared. Every instance of a string of up to two letters in common adds 1 to the total score. For sequences of three or more characters, the longer the identical sequences, the exponentially higher the score. After comparing all the strings in text "A" with all the strings in text "X," the program registers the resulting score in a record that might be called "comparison with text X" in a file that might be called "comparisons against text A." Then the program proceeds to compare text "A" with text "Y," and so on.

The COMPARE command can be used to retrieve texts that are essentially the same, even if they differ in spelling, orthography, or punctua- tion. It makes a database immune to the pitfalls of typing errors, and it is indispensable when dealing with texts from a variety of sources and from periods before standardization of languages. How- ever, its principal use in our databases is to find instances of text paraphrasing.

The programming is done in a unique inter- active mode that is semi-automated and prevents many of the most common errors. In general, lines of programming take the form of complete, intelligible English-language sentences. Tasks can easily be programmed for reading data from, and

exporting data to, external ASCII files. Data can easily be imported or exported via modem with special commands without leaving the Savvy PC database.

Savvy records can have up to 254 fields. The length of fields is not specified in advance and can be up to 1,000 characters. Files can have up to 60,000 records, but files can contain file names, so that, in effect, the database might include as many as 3,600,000,000 records. The larger of the two databases described here has 3,706 records and occupies a little more than six megabytes of storage memory, comfortably housed on a hard disk and conveniently backed up and transported on six high-density 5.25-inch floppy diskettes.

The Index of Arias in Vivaldi's Operas Vivaldi was a typical opera composer of the early eighteenth century in that he borrowed heavily from his own and others' works} Frequently the motivation for the borrowing was to include, in a given singer's role, arias that she or he had previ- ously learned for another opera, thereby saving time and effort for a singer who might have to learn three or four new operatic roles in the autumn and carnival seasons each year. These roles were rarely repeated, as in today's repertoire opera theater; instead, individual arias were re- peated, but in a new context and often with new words.

The fascination of this system of borrowing and retexting is, paradoxically, that it gives us insight into the relationship between music, text, and drama from the point of view of the composer and his poet. If, for example, the same music is used to set one text expressing joy and another text expressing rage, the essential point of contact between music and text in both cases is the expansion of the life spirits (activity, animation) that is occasioned by both passions (according to the aesthetics of the time) and is suitably projected by such features of the music as fast tempo, rapid rhythms, wide intervals, and loud dynamic level. Often, however, the common ground among several texts and their common music is more interesting and subtle. Many examples are dis- cussed in the literature cited in footnote 2.

The database described here is used to find which of Vivaldi's arias were used in more than

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one opera. The task would be simple if all the operas survived in score, but in fact out of some 125 productions of operas by Vivaldi or of operas that used his arias, only 21 can be associated with surviving scores. (For many, there may never have been a complete score -- the recitatives from some earlier setting of the same text may have been used with individual scores of arias taken from still other operas.) For the remainder, only a libretto survives. The borrowings can still be traced, however, for with rare exceptions the presence of a borrowed text indicates that music, too, was reused. On the other hand, we noted earlier that the borrowed text was usually modified. The changes in the texts of borrowed arias frequently occur in the first poetic line, which makes the alphabetical list of first lines -- a standard tool for the past century of literary, musical, and theater scholarship -- practically useless. Nevertheless, with the COMPARE command, the matches shown in Example 1 can be found. As a result, one can conclude that Anna Cosimi sang "Parto confusa anch'io" in Vivaldi's 1739 Siroe to the same music with which she sang "Ardo ferita, oh Dio" in Vivaldi's 1738 Orlandofurioso. The same result, of course, could have been achieved with an index of verse scansion, but it required a com- puter-based index to find the text relationships shown in the second and third matches under Example 1, because the configurations of lines are not the same. These examples have been chosen from many dozens of others to exemplify two obviously similar texts, a highly probable case of elaborate parody, and a case that requires non- textual supporting evidence: Antonio Denzio, who sang both texts, was the impresario in Prague, and frequently used Vivaldi's arias. The libretto of La tirannia castigata ascribes all of its arias to Vivaldi, the recitatives to Antonio Guerra. Furthermore, twenty-nine of the thirty-five aria texts in La tirannia castigata are parodies or literal quotations of aria texts in La costanza trionfante. Based on the series of comparisons and searches conducted so far, we can anticipate that new instances of parody will be identified in every opera that Vivaldi produced, typically five or six new instances in each production.

The Vivaldi opera aria index incorporates text data that were created with word processors on

several different types of computers. Most of this data was transferred to an IBM PC-AT via a direct cable connection between serial ports. The result- ing ASCII file was edited then read into the database. The index program compares texts, individually or in groups, and returns the most probable matches to a queue (actually a file whose name identifies the matrix aria text). Probable matches are then displayed side by side, and the operator is prompted to choose, based on addi- tional criteria, whether to accept or reject the match. Accepted matches are recorded in another file and can be exported to an ASCII file for printing or incorporation into the text of a paper, article, or book. (The necessity of using a rela- tional database is, thus, evident. Each aria record in the main file is associated with two subsidiary files: one to record probable paraphrases, the other to record accepted matches.)

Naturally this database can be searched and sorted for opera title, city, year, season, theater, composer, poet, singer, character, act, scene, aria number, musical source (if any survives), versifica- tion, and first line of aria text in any kind of Boolean combination, just as in several other databases of opera libretti? Its unique features, however, are the inclusion of complete aria texts - - not just first lines -- and the ability to find text paraphrase relationships that would be impossible to locate using a Key Word Index Concordance, upon which all other libretto databases rely.

This database and its programmed tasks are currently undergoing final adjustments in prepara- tion for a full round of comparisons between each text and every other. Relying on frequent disk access, that process would require four months of continuous operation. We are looking into using extended memory as a RAM disc and a faster clock speed. With OS/2, which will enable data- base programs to address extended-memory and the new generation of MS-DOS machines based on the 80386 chip, even larger databases like this and with similar purposes will be feasible.

Connect ions among Fifteenth-Century Central- European Mus ic Treatises A significant number of music theory treatises concerning both chant and measured polyphonic music are preserved in manuscripts copied in

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108 JOHN W A L T E R HILL AND TOM R. W A R D

Two obviously similar texts:

Siroe rd di Persia (Ferrara, Carnevale, 1739), 1/16/1 Laodice sung by Anna Cosimi Configuration of lines: 7 7t 7t 5 7 7 7 5

Parto confusa anch'io Ne s6 quel che sarh; Non bo pi~ libert~t, Non ho pi~ pace. Vorrei del fato mio Scoprir quall'b il tenore, Ma timido il mio core E pena, e tace.

1l Tamerlano (Verona, Carnevale, 1735), 2/10/1 ITn, Giordano 36 A 4 Configuration of lines: 8 8 4 8t 8t 8 8 4 4 4 5 8t 8t 8t 8t 8t 3 5 3 4

Si crudel! questo b l'amore D'un tiranno, inique core. Mostro indegno Dispietato senza ft. Morte al padre, oh Dio! perchb Cosi barbara sentenza? Non b degno di clemenza Tanto fasto Tanto orgoglio Morte attendi E morte voglio Numi, aita oh Dio! pieth. Nb non sh, che sia pieth. Io non voglio sua pieth. Nb non merita piet~t. Questa ~ troppo crudelth. Pur al fin La mia morte Pur al fin Nostra morte.

La costanza trionfante (Venezia, Carnevale, 1716), 1/02/1 Artabano sung by Antonio Denzio Configuration of lines: 9 8 8 8 8

Arda l'ira, lo sdegno avvampi Tutto sia cenere, e polve. Col depor l'empio dal foglio Resti vinto il fiero orgoglio, Ch'un tiran mai non s'assolve.

Orlandofurioso (Vicenza, 1738), 1/01/1 Angelica sung by Anna Cosimi Configuration of fines: 7 7t 7t 5 7 7 7 5

Ardo ferita, oh Dio, N~ so quel, che far~ Non b pi/1 libertY, Non 6 pih pace. Fa, si, che l'idol mio AI sen mi torni amante, ma quant'io son costante Alla sua face.

Elaborate parody:

Armida al campo d'Egitto (Venezia, Carnevale, 1738), 2/14/1 A 4 Configuration of lines: 8 8 8t 8t 8 8 4 4 4 5 8t 8t 8t 8 8 4t 5 5 8t 8t 8t

Morte a me Fiero rigore Mi condonna traditore.

Non sei degno di merc6. Numi, cieli, oh Dio! Perch~ Cosi barbara violenza? Donna rea ta mia innocenza Tanto fasto? Tanto orgoglio? Morte attendi E morte voglio Morte, oh Dio! Ah n6 pieth. Non ~ tempo di pieth. Questa ~ troppa crudelth. La costanza, o la fortezza. I1 rigore, la fierezza. Del tuo cor. Della mia sorte Dell'alma ingrata La tua morte abbatterh. La tua morte appagherg. La mia morte appagher~.

Requires nontextual evidence:

La tirannia castigata (Prague, Carnevale, 1726), 1/01/1 Nerone sung by Antonio Denzio Configuration of fines: 8 8 8 8 8

Ate riedo, o Campidoglio Cinto il crin di verdi allori. Gi~ del Ponto il fiero orgoglio Vinto abbiamo, & ~ quel foglio Bel trofeo de miei sudori.

Example 1. Matches provided by the Vivaldi aria index.

cen t ra l E u r o p e d u r i n g the f i f teenth cen tury . T h e s e t reat ises i n c l u d e the works of i n t e r n a t i o n a l l y k n o w n writers , pa r t i cu l a r ly J e h a n de Mu rs , b u t

they also p r o v i d e a b o d y of i n f o r m a t i o n that s eems to have b e e n f o r m u l a t e d b y far less w e l l - k n o w n wri ters w o r k i n g in this region . A few of these

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treatises have been investigated, and several have been published. However, insufficient attention has been paid to the interrelationships among all of these works and to the source of the material common to all or some of the treatises. 4

It seems that a rather obscure writer, cited as an authority in several of these central European treatises, was a member of the faculty at the University of Prague during the 1360s. 5 In the process of tracing references to him, Ward iden- tified a number of treatises that contain related musical material. Only half of these treatises have been edited and only a few of the relationships have been made known. The task of comparing each treatise with every other in order to find all identical passages, all similar, but differently worded passages, and all instances of similar manners of presenting or explaining was daunting. Finding all identical passages by sight would involve line-by-line comparisons. Similar passages could be found in this way only with difficulty and with a large expenditure of time. It is yet more difficult to find instances of similar procedures in setting out the information on different topics. All of these kinds of relationships are present among the treatises.

The solution to the problems of making numer- ous comparisons was alleviated by employing a relational database management system that in- cluded a facility for finding similar sentences in individual treatises, since in only a few instances are there identical statements. Most database systems allow us to find identical content of fields or search for identical strings, but they do not indicate the degree of similarity between two nonidentical strings, in this case between any pair of sentences. Savvy PC was used because its COMPARE function provides a number related to the degree of similarity of the strings compared. This made it possible to find sentences of varying degrees of similarity and to order these by the degree of similarity using the number generated by the COMPARE function as an index field.

The texts of the treatises were entered and saved as an ASCII file so as to avoid problems with control characters used in formatting. This made editing of the texts a much simpler task, since the database was not involved. These files were then read into the database and stored as files. During the import procedure, the individual

treatises were read into individual files named by the identifying siglum for the treatise. Each file contained one treatise, and each record one sentence. The sentences of the treatise are num- bered, following standard practice in editing these texts, and that number also serves as the record number within the file, making possible rapid access to specific sentences. A related file, created as a part of the import procedure, contains full citations of the source of the treatise (library, call number, pages/folios, etc.) and a second related file contains literature concerning the treatise or the manuscript in which it is located. The file names are also added to a master list of treatise files.

Separate programs allow for editing of the texts once they have been incorporated into the data- base and for saving the results. This task can also be accomplished by moving the text back into a word-processing environment, editing it, and then returning it to the database. Depending on the nature of the editing involved, each of these proce- dures has its advantages and disadvantages.

The major operation of the system is the generation of a file containing pairs of similar sentences and an indication of the degree of similarity between each pair. The comparison of sentences operates by comparing each sentence with every sentence in every treatise. The com- parison results in a number (score) that represents the degree of similarity among the sentences. A threshold value is used to determine whether the degree of similarity is sufficient to warrant saving a record of the pair. (This eliminates those pairs that contain one or two identical words but which have nothing significant in common.) If the score exceeds the threshold value, a record containing the treatise siglum and line number for each sentence (not the entire text) is added to the "Similar Lines" file, and the score is used as the key field, so that the file is ordered in ascending fashion by degree of similarity.

This file must be edited to weed out only superficially similar matches. The comparison function is influenced by the lengths of the strings being compared and the exactness of correspond- ence, including placement of the similar string within each sentence. Thus, a pair of sentences in which one sentence in one treatise appears as a clause in a longer sentence in another treatise may

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1 1 0 J O H N W A L T E R H I L L A N D T O M R. W A R D

generate a lower score than a pair of sentences that are unrelated in substance but which share a common phrase occurring at the beginning of each, e.g., "Et est diffinitur sic:. ' '6 Those pairs of sentences in which the word order is significantly different (something not uncommon in medieval Latin) will also occasionally generate a somewhat lower score than might be expected, requiring that the threshold be lower than one would otherwise want. A program step to eliminate some of the most common phrases could be added to reduce the frequency of spurious matches, but, for the moment, the editing step remains the means of dealing with this problem.

A second file, "Multiple Matches," is generated by collating the matches listed in "Similar Lines." Each record in this file is the list of all matches to a given line. The file is created by searching similar lines for multiple occurrences of a sentence and putting all matches for that sentence into a single file. Multiple Matches contains, then, all of the material common to more than two of the trea- tises. The data in Similar Lines and Multiple Matches (and in other files referring to specific lines of treatises) is not the entire text string but rather the manuscript siglum and line number separated by a dash. This reduces the storage required for the files and allows for much quicker searches using pattern matching rather than degree of similarity. Display and printing programs use this information to find the specific line in the appropriate treatise file.

Additional programs have been created to form indexes that list occurrences of specific words (including variant spellings of these words) or to locate specific words or phrases. Related words, those sharing a stem but with different gram- matical endings, can also be located. These functions aid in isolating discussion of topics or the use of characteristic manners of expression. Additionally, the program can print out any single treatise with concordant lines from any or all of the other treatises interspersed in a contrasting type size to facilitate comparisons of readings. By presenting all concordant readings, this last func- tion can be of enormous value in completing the editing of a treatise in which the hand and/or abbreviations in the source are not immediately understandable. It is also useful in generating the

text and references for a critical edition. In the latter case, the file can be "printed" to disk for use in a word processing environment that would allow appropriate formatting, insertion of foot- notes, etc.

The principle developed in the Vivaldi aria index has been used by John Hill and his students in other databases to find instances of text para- phrase as evidence of reuse of music in early sixteenth-century Italian laude, in sixteenth-cen- tury theatrical interludes (intermedi) in relation to associated madrigal repertoires, and in early seventeenth-century solo songs (monodies) in relation to theatrical productions in Italy. Tom Ward's music treatise index program is serving as a model for further work by graduate students, several of whom are researching the use of recurring phrases and paraphrasing in the texts of Renaissance motets. The same basic strategies could be used to locate similar strings of musical notes in alphanumerical representation or of any other symbols. This research method uses simple, inexpensive software and widely available hard- ware, and readers with imagination will undoubt- edly find many other uses for it, within the field of musicology and beyond it.

Treatise File il

1

i L. MATCH 1 (SIGLUM-ID) , i MATCHn

mille LIBRARyCITYcALL5 I aLl IMNo. i <-~I

~I [word] (SI~LUM-ID]

WORDS INDEXED II

i i

Figure 1. The structure of the music treatise database.

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D A T A B A S E S FOR T E X T P A R A P H R A S E S IN M U S I C O L O G Y 111

Notes i Excalibur Technologies Corporation, 122 Tulane S.E., Albuquerque, NM 87106, (505)265-1273. Savvy PC, which is very inexpensive, seems no longer to be offered by retailers that advertize widely. It can be ordered directly from Excalibur, whose representative recently mentioned their current development of a version of Savvy for VAX machines. 2 The process in Vivaldi's operas is described in John Walter Hill, "Vivaldi's Griselda," Journal of the American Musico- logical Society (1978), 53--82; Hill, "Vivaldi's Orlando: Sources and Contributing Factors," Opera and Vivaldi, ed. Michael Collins and Elise K. Kirk (Austin, 1984), pp. 327-- 46; Hill, "Vivaldi's 'Ottone in Villa' (Vicenza, 1713): A Study in Musical Drama," in Domenico Lalli-Antonio Vivaldi, Ottone in villa, Drammaturgia musicale veneta, 12 (Milano, 1983), pp. ix--xxxvii; and Eric Cross, The Late Operas of Antonio Vivaldi, 1727--1738 (Ann Arbor, 1981), 57--80. A general treatment for Vivaldi and his contemporaries is Reihnhard Strohm, Italienische Opernarien des friihen Settecento (1720--1730), I, Studien, Analecta Musicologica, 16/I (Ktln, 1976), 245--60. -~ All other databases of libretti known to the authors are limited to these bibliographical elements or some subset of them. They are the "Index of Libretti for Sacred Vocal Works performed in the Venetian Ospedali" by Jane L. Berdes (Bethesda, MD), "U.S.-RISM Libretto Project" by Marita P. McClymonds (University of Virginia), "Searchable Index of Venetian Opera Arias" by Sylvie Mamy (Paris), "Libretti of Works Performed in Bologna, 1600--1800" by Mario Baroni (Bologna), "Neapolitan Comic Opera Libretti, 1700--1750" by Francesco Degrada (University of Milan), "Database for Eighteenth-Century Italian Opera" by Dale Monson (Univer-

sity of Michigan). None of these databases contains complete texts of arias, and none, therefore, is capable of matching texts that are in any degree similar if the first lines are different. 4 The editions include C. E. H. de Coussemaker, Scriptores de Musica for the treatise known as Anonymous XI; W. Gieburowski, Die "Musica Magistri Szydlovite" (Posen, 1915); Dtnes yon Bartha, Das Musiklehrbuch einer ungaris- chen Klosterschule in der Handschrift yon Fiirstprimas Szalkai (Budapest, 1934) for the treatise copied by Ladislaus Szalkai; Johann Amon Der "Tractatus de musica cure glossis" im Cod. 4774 der Wiener Nationalbibliothek (Tutzing, 1977) for the anonymous treatise preserved in Vienna, National- bibliothek, MS 4774. In addition, Bartha's study of the relationships among the treatises related to that copied by Szalkai ("Studien zum musikalischen Schrifttum des 15. Jahrhunderts," ArchivfiirMusikforschung, 1 (1936), 59--82 and 176--99) marked an early, albeit incomplete, essay at comparison. s Tom R. Ward, "The Theorist Johannes Hollandrinus," Musica antiqua VII (1985), pp. 575--98. All other discus- sions of this theorist and his writings on music, particularly of mnemonic verses attributed to him, are incorrect. 6 The definitions of intervals are a particular problem since a characteristic of the treatises is the formulaic description of intervals as ]Interval] "est diffinitur sic: est saltus ab una vocum in [distance and further characterization of interval]." The compare function generates a relatively high score for this because the common words occur in the same relative position in each interval definition. The matches discovered in this way are saved for further research because they are of use in investigations of similar uses of language in the treatises.