Damien SAGRILLO Zurich 9 July 2007 1 In my lecture I will not present a concluded work, but a set of ideas in progress that I hope to finish one day by landing an adequate fund for a research project. Since about two decades I m dealing with folksong research. Since this time I encoded about 1200 folksongs of Luxembourg, the French region Lorraine and Ireland. Recently I finished a work on Scottish folksong. This study was a part of a research project in historical musicology about Haydn s arrangements of folksongs of the British Isles commissioned by the University of Luxembourg. 1
Towards an Atlas of Folksong Idioms EsAC (Essener Assoziativ Code) Analysis of Scottish Songs Atlas of (European) Folksong Idioms 2 In my lecture 1. I will first begin with a short description of EsAC and give a short overview about the last EsAC activities; 2. then I will report about my latest investigation on Scottish folksongs and 3. present my idea of an atlas of European folksong (Idioms) 2
1 EsAC Helmut Schaffrath (1942-1994) EsAC for encoding & Essen software for analysing one part songs ICTM Study Group of Computer Aided Research http://www.ictmusic.org/ictm/beta/stg/index.php?lcode=3&tcode=63 http://ulrich-franzke.de/seiten/schaffrath.html 3 EsAC, the Essen Associative Code was invented by Helmut Schaffrath in the 80ies. It was inspired by the Chinese Jianpu code. Until his death in 1994 Schaffrath encoded and also encouraged encodation of songs and developed archiving, representation, retrieval and, most important, analysing software. 1. Until today about 10.000 songs are encoded in EsAC 2. A the same time this software package was joined and became publicly accessible. What were the last ESAC activities? Helmut Schaffrath founded the Study Group of Computer Aided Research of the ICTM in 1985 and held the chair until his death in 1994. The aim of the group is to promote the computer as a tool of archiving and analysing one part music. In 1995 Ewa Dahlig took the chair, and several meetings were organized, mainly in Poland. The last meeting took place in September 2004 in Vilnius. During this time ESAC-data and software were in constant use. 3
1 EsAC EsAC Scottish song Todlen Hame, 1rst phrase ESSEN ANALYSIS SOFTWARE 1 statistics of intervals and degrees 2 statistics of rhythm and durations 3 phrasing, range, scales and number of phrases 4 order of accent tones and order of final tones of phrases 5 melodic contour, melodic and rhythmic structure 4 Here is the ESACode as we know it. Tone degrees are orientated on the fundamental and rhythm on the shortest unit, in this case the semiquaver. The ESSEN ANALYSIS SOFTWARE gives the following information: 1 statistics of intervals and degrees 2 statistics of rhythm and durations 3 phrasing, range, scales and number of phrases 4 order of accent tones and order of final tones of phrases 5 melodic contour, melodic and rhythmic structure 4
Todlen Hame in ESAC and analysed by Essen Software 1 EsAC 5 and here we have an analysed data record of the song Todlen Hame. I will shortly describe once more the four steps with the help of this illustration: 1. lines 147-151: the software input of statistics of intervals and degrees 2. lines 152-155: the software input of statistics of rhythm and of durations 3. lines 156-167: the manual input of song title and further required information as signature, key and time; the software input of rhythmic model and the number of phrases 4. lines 168-174: the software input of scale & range, the order of cadence & accent tones, the melodic & rhythmic structure, the melodic contour and finally the phrasing (upbeat or not) 5. lines 175-176: the manual input of remarks plus my input of the song structure 5
Todlen Hame 1 EsAC 6 and here we have the song in note form 6
2 PURPOSE Prospective Atlas of European Folksongs informing about geographical idioms Two main tracks 1 drawing melodic contours 2 distinguishing song structures 7 My Ideas of an idiomatic folksong atlas: Two main strategies will be embarked: 1.strategy: drawing melodic contours; for this purpose however the Essen software must be tailored to my need. First my opinion about melodic contours: I don t appreciate this term, because it connotes too much with a graphic assessment. In German you would say melodischer Verlauf. This expression seems to be more adapted and could be translated with melodic progression and reveals more adequately the time aspect of music. 2.strategy: distinguishing song structures; for this purpose the Essen software can be applied without change, but with some caution, as we will see soon. The atlas will help to find an answer to the question if there are common traits in several folksong groups and what are the typical national and regional characteristics? The method of my investigation should be a three step combination of automated preparation, including a preclassification of the data and of non-automated musical interpretation It is however important to notify that a large amount of routines still remains to be automated, and this could simplify enormously the working process and help to save time! 7
2 PURPOSE Form analysis by Essen software Todlen Hame 8 We see the importance of a final decision by the musical thinking and feeling human being in comparison to the measurement of similarity by the machine at the example of the song Todlen Hame. The structure of a song is defined by the number and the repetition of phrases. Songs with more repeated phrases have a strong internal relationship, with few new musical elements. Songs with less inner repetitions have on the other hand a weaker consistency. When we look at the song and at the software analysis wee see that 1. the software considers a dual phrase structure and separates melodic progression from rhythm 2. we also can see that the software analysis indicates four different melodic phrases (a to d) and three different rhythm phrases (a to c) A combination of rhythm and pitch analysis seems to be hardly feasible by computers! 3. while the attribution of the rhythm structure is exact, the melodic structure allocated to the song is doubtful 4. all the phrases with the exception of the third phrase are comparable with smallest divergences 5. this song has a strong inner consistency, which however gives the listener the impression of a tiresome monotony! 8
3 (EXPECTED) RESULTS Restrictions for this presentation and therefore the term Towards in the title 51 songs of Scotland 62 songs of Ireland 503 songs of Lorraine 615 songs of Luxembourg This is not a well balanced mass 9 I will now point out some results of my investigation, which for this moment consists only in a more or less concrete idea with an outcome that shows the need of further efforts and therefore I have to make the following restrictions: 1. before providing dialectological attributes of a folksong territory, we should have a critical and well balanced mass of (let s say about at least 200) songs of the several regions, 2. for the current research this critical mass was only realized for the folksongs of Luxemburg and Lorraine, but not yet for Ireland and Scotland, 3. the regions should be comparable in size 4. the sources should be as different as possible. Often one single source supplies stereotype data. (This problem appears for instance in the German song collection of Louis Pinck in Lorraine) 5. further regions need to be added 9
http://www.vysoketatry.com/mapy/europa/europa.gif 3 (EXPECTED) RESULTS 10 At this moment we have folksongs encoded from a lot of regions of Germany; yet it is regrettable that they are not assigned to specified regions. Aarden & Huron detect this weak point in the Essen collection with good reason in their article Mapping European Folksong Ewa Dahlig has encoded more than 1500 songs of Cassubia It is indispensable that other regions of Europe are considered: Central Europe; Poland; the Baltic states, Hungary, the Alps region, France, the Iberian peninsula, the Scandinavian countries, south eastern Europe, Russian folksongs (but in a limited regional clearly delimited selection) Songs of other cultures could also be integrated in this atlas: the pentatonic songs of the negro spirituals vs. Chinese pentatonic songs for instance. As far as I know, we also have encoded songs from the Baltic countries and from the Czech Republic It would be very important to have songs from Hungary; Bartok and Kodaly have published, systemised and analysed thousands of songs in the Corpus Musicae Popularis Hungaricae. An orientation to these results could help to improve the Essen analysis software. 10
The length of the songs in phrases 3 (EXPECTED) RESULTS 11 This study, as a first step, informs about Scottish style in comparison to the style of the other three regions. I will not present all the results, but I will limit myself to the most essential conclusions, in bringing up some significant attributes of Scottish folksongs: 1. Compared to folksongs of the continent, Scottish songs are long, very long. They have 8 phrases, while the songs of the other regions have an average of 4 phrases (see on one of the next slides). 2. We also can perceive the comparability between the folksongs of Lorraine & Luxembourg. Most of them have 4 to 8 phrases (in decreasing order: 4- phrase, followed by 6-phrase, 5-phrase and 8-phrase songs; 7-phrase songs being an exception) 3. Concerning the songs of Ireland we can observe that one fifth (21%) have 8 phrases, the second highest value 4. One possible conclusion: folksongs of all regions prefer an even number of phrases! 11
Main structures 3 (EXPECTED) RESULTS 12 This table shows the number of different phrases in folksongs. Example: the eight phrase song with the structure A1-A2-B-A2-A3-A2-A3-A2 has two different phrases and an important inner consistence, whereas the song with the structure A-B-C1-D-E-F-C2-D with six different phrases has a weaker inner consistence. 12
3 (EXPECTED) RESULTS Range 13 The range of Scottish songs is very important, i. e. an 11th. This is one of the reasons, why Scottish songs often give the impression of a composed air for a professional performer rather than a simple folksong for an amateur singer. 13
Further characteristics of Scottish songs dotted rhythms the Scots snap 3 (EXPECTED) RESULTS 14 Further characteristics in Scottish folksongs are: dotted rhythms and Scots snaps; Collinson, in his book about Scottish folksongs, names it this very life-blood of Scots musical rhythm 14
4 THE PROSPECTIVE ATLAS The catalogue of melodic progression (1) 15 The first step of an atlas of folksongs will be a catalogue of classified phrases of folksongs First remark: The way to this atlas will be achieved by a catalogue of folksong phrases in three steps (It would be too time-consuming to expose the exact scheme of this catalogue now, and so I will only give this information). I choose the method of segmentation of folksongs into phrases, to be able to classify and to interpret musical progression free from musical structures! 1. In a first version of this catalogue I ll give myself a sort of rough template with all data adequately prepared. 2. In a second version I will sort these data by machine according to quantifiable criteria. 3. Finally I will adjust this second version after musical standards and appreciations to come to an intelligible, unequivocal classification. Second remark: For reasons of comparability, all melodies are transposed to one single key, namely to G! The catalogue begins with phrases of low range and ends with complex phrases with changes of melodic directions and vast ranges. The disadvantage is, that interdependence between phrases of low and of high range must be specified in annexed textual explications. But the practise has shown that relationships of this kind are exceptional. The folksong atlas will illustrate melodic progression and structures in a final layout with a scope from the most typical to less typical folksong groups for every region. This excerpt reveals typical traits of Luxemburgish folksongs. Similar notes are represented in a vertical order. We can observe in this passage the characteristic -5/1-upbeat and an ascending section to the third degree, 15
4 PROSPECTIVE ATLAS The catalogue of melodic progression (2) digital version (1) 16 Here we see the digital form of the catalogue. In addition to the previous passage, folksong phrases of Lorraine are added here. This juxtaposition of melodic progressions gives us indications about regional distinction. So we can see inside the red border some phrases of Lorraine beginning at the fundamental, descending to the 6 th degree, ascending again to the fundamental and descending finally to the 5 th in overstepping the 6 th degree. As we can see at the neighboured phrases, this melodic progression does not exist in the folksongs of Luxembourg. Here the 7 th degree is leaved out. 16
4 PROSPECTIVE ATLAS The catalogue of melodic progression (3) digital version (2) 17 On this slide we see a common melodic progression in folksongs of Luxembourg and Lorraine (inside the red border). It resembles to the beginning of the song Fuchs, du hast die Gans gestohlen 17
4 THE SONG ATLAS 4 PROSPECTIVE ATLAS showing a typical Scottish song: Nanny O 18 The classification of the entire songs will be deduced from the previous sorting of the single phrases and will begin with the most typical song, resp. song groups of each region and continue to less characteristic exponents! 1. For the Scottish songs the following characteristics can just yet be emphasized: 2. Scottish songs are long and have symmetrical structures (8 phrases)! The number of different phrases of this song is 6! 3. Nanny O has an immense range of a 13 th. Large intervals, both ascending and descending mark the melodic line of Nany O with a typical ascending minor sixth at the end of the third and seventh phrases (bars 6 and 14) and in the bars 9 / 10 and 13 and furthermore the descending 5th and octaves at the end of the phrases 2, 4, 6 and 8. In addition to the large intervals comes an important range of a thirteenth that cannot be mastered by an amateur singer. 18
4 PROSPECTIVE ATLAS Nanny O 19 Scottish songs very often change to the high register in the second part (phrase F). In the songs of Central Europe this phenomenon is called Metatyp. The term Metatyp has been coined by the German Folksong Archive (DVA) to describe melodies which have their highest tone in the third phrase, e. g. in the second part of the song [STIEF]. Typical song incipits: a part of songs are beginning with a -5/1 pattern, with the fifth degree as upbeat. This model is also very common to central European songs and occurs especially in faster melodies. Less common, e. g. more distinctive Scottish, are beginnings of songs in slow movement with three steps up or down, followed by a larger skip or a change of the melodic direction, whether by step or by skip. These figures can be found inside the songs as well. (Examples of ascending incipits are: 345121, 12321, 123-5-61 Examples of descending incipits are: 32135, 321543) The scales in the automatic analysis program are qualified, but often the identification is dubious. However the numerical characterisation of tonal steps is beyond doubt. A lot of the songs of Scotland are more developed and sophisticated with a majority being completely diatonic with scales of seven and more tones. Scottish tunes have diverse tonalities from pentatonic to modal scales (COLLINSON pp. 4-10). Typical Scottish songs are those with pending tonalities between major and minor, respectively between other scales, as we can see here in the example of Nanny O. The phrases A/D & F are in c-minor (zeigen), and the phrases B/C1/E & C2 are in Eb-major. (For the determination of this arcane tonality the Essen software will surely have problems). 19
4 PROSPECTIVE ATLAS and showing a typical Luxembourgish song Eim Steffen 20 1. This typical Luxembourgish song has four phrases 2. The number of different phrases is 3 3. The range of this song is an 11 th ; but this is due to the upbeat. Without this upbeat, the range would be an octave and correspond to the average, 4. Eim Steffen begins with an upbeat -5/1, and the b-phrase has a less typical reverse upbeat +5/+1; this is standard for song beginnings in Luxembourg and seems to be a clear indicator for folksongs of Central Europe in general. 5. The example from Luxembourg has a diatonic five tone scale (degrees 1 5), without being a pentatonic song because of the occurrence of the semitone step 3/4. The sixth and seventh degrees are missing. 20
5 OUTLOOK thank you for your attention Damien Sagrillo 21 Comparing folksongs of Luxembourg and Lorraine and at the same time Irish folksongs with the folksongs of Scotland seems to be rather hazardous. But the numerical investigation represented in the tables confirms a certain coincidence between the folksongs of Luxembourg and Lorraine, relating for instance to the number of phrases. But I m sure that a more detailed investigation concerning melodic characteristics would find a relative proximity of Irish to Scottish songs. The computerised analysing method is not inapt, but more time is required. After analysing and classifying hundreds of folksongs from Luxembourg and partially from Lorraine and after comparing Scottish songs with the songs of the three other regions, I found that the method of comparing folksong segments is a very effective instrument to find dialectological characteristics. But the method is not fully automated; it needs the interaction of the musical researcher with the machine. The question, if it would be preferable to invent a fully computerised system of folksong analysing is easy to ask. Unfortunately I m not enough mathematician and computer specialist to give an adequate answer. On the one hand the gain of time would be remarkable. All the time consuming procedures could be abbreviated, and as matter of fact, there are numerous stereotype steps that are suitable for mechanisation. On the other hand the inadequacy of a fully computerised song analysis cannot be ignored. It is proved by some unsuccessful attempts of demonstrating melodic similarity. However the studies are numerous dealing with completely automated analysing software. 21 Finally I am sure that, after adapting EsAC to contemporary needs and with