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The Structure of VerseFormal, experimental and computational approaches
19–20 March 2015
Leiden University
Local organisersAnne Rose HaverkampMarc van OostendorpTeresa ProtoVarun. deCastro-Arrazola
Thursday 19 March
Where: Lipsius building (Cleveringaplaats 1), room 147.
Special topic: Encoding and decoding verse: structure and perception of metered poetry.
09:30 Nigel FabbThe metrical line in working memory
10:30 Coffee break
11:00 Kristin HansonMetrical Tension Revisited
11:30 Tomas RiadMeter as improvement
12:00 Francois DellMeters, performance templates, and their interactions
12:30 Poster session (& lunch break)
14:30 Romain BeniniThe metrical ambivalence of lines in 19th century French songs
15:00 Jean-Louis ArouiA Template for a Classical Arabic Meter: the Kamil
15:30 Tatyana SkulachevaVerse and prose: linguistic regularities which differentiate them and their possibleinfluence over human brain
16:00 Coffee break
16:30 Svetlana Bochaver & Dmitri SitchinavaThe Spanish Verse Corpus
17:00 General discussion
19:00 (approx) Social dinner at Oudt Leyden (Steenstraat 49)
Friday 20 March
Where: Lipsius building (Cleveringaplaats 1), room 147.
Special topic: Encoding verse digitally: how to build, use and connect corpora.
09:30 Kevin RyanExpected frequencies in verse
10:30 Coffee break
11:00 Dan BrownThe Rhyme Analyzer toolkit, and its use in analysis of lyrics and poetry
11:30 Petr Plechac & Varun. deCastro-ArrazolaXML schema proposal for encoding verse digitally
12:00 Marlein van RaalteThe Phenomenon of Bridge in Greek Stichic Verse
12:30 Lunch break
14:30 Stefano Versace, Lilla Magyari & Mark DingemanseVerseTyp 2.0: A Database of Verse Forms in the Languages of the World
15:00 Michael Cade-StewartUsing MARY text-to-speech to determine Rhythm and Metre in English Poetry
15:30 Paolo BraviThe genetics of oral texts. Empirical findings and ethnographic investigation in thefield of Sardinian improvised poetry
16:00 Coffee break
16:30 Varun. deCastro-ArrazolaA repository of verse templates
17:00 General discussion
Poster session
When: Thursday 19 March, 13:00.
Where: Lipsius building, ground floor, between rooms 003 and 005.
Klemens Bobenhausen & Benjamin HammerichMetricalizer3: Automated Metrical Analysis for German Language
Andrew CooperA moraic analysis of the Old English metrical line
Kristen de JosephRig-Vedic metrics: A constraint-based approach
Pablo GervasWorking on the Automatic Scansion of Verse
Elena Gonzalez-Blanco & Clara I. Martınez CantonReMetCa and DIREPO: Poetry standardization through a common ontology
Megan HartmanGnomic Meter in The Wanderer and The Seafarer
Tetiana ShkurkoEnglish vers libre prosody (auditory analysis results)
Olga SozinovaRhyme properties in the material of Marina Tsvetaeva
Participants
Aroui, Jean-Louis [email protected] University, UMR 7023 Structures Formelles du Langage
Benini, Romain [email protected] 5611 LIRE / Paris III – Sorbonne Nouvelle
Bobenhausen, Klemens [email protected] Communication & Consulting GmbH
Bochaver, Svetlana [email protected] of Linguistics, Russian Academy of Sciences
Bravi, Paolo [email protected] di Musica G. P. Palestrina, School of Ethnomusicology, Cagliari (IT)
Brown, Dan [email protected] R. Cheriton School of Computer Science, University of Waterloo, Canada
Cade-Stewart, Michael [email protected] of Digital Humanities, King’s College London
Cooper, Andrew [email protected] of English, Stockholm University
deCastro-Arrazola, Varun. [email protected] University & Meertens Institute
de Joseph, Kristen [email protected] University
Dell, Francois [email protected] de Recherches Linguistiques sur l’Asie Orientale (CRLAO), CNRS / EHESS,Paris
Dingemanse, Mark [email protected] Planck Institut for Psycholinguistics, Department of Language and Cognition
Fabb, Nigel [email protected] of English Studies, University of Strathclyde, Glasgow
Gervas, Pablo [email protected] de Informatica, Universidad Complutense de Madrid
Gonzalez-Blanco, Elena [email protected] (The National University of Distance Education in Spain)
Hammerich, Benjamin [email protected] Zurich
Hanson, Kristin [email protected] of California, Berkeley, CA, USA
Hartman, Megan [email protected] of Nebraska at Kearney
Magyari, Lilla [email protected] Peter Catholic University, Faculty of Humanities and Social Sciences,Department of General Psychology
Martınez Canton, Clara I. [email protected] (The National University of Distance Education in Spain)
Plechac, Petr [email protected] of Czech Literature, Academy of Sciences of the Czech Republic
Proto, Teresa [email protected] University
Riad, Tomas [email protected] University, Stockholm, Sweden
Ryan, Kevin [email protected] University
Shkurko, Tetiana [email protected] National Academy of Building and Architecture (Foreign LanguagesDepartment), Ukraine
Sitchinava, Dmitri [email protected] of the Russian Language, Russian Academy of Sciences
Skulacheva, Tatyana [email protected] Institute of Russian Language, Russian Academy of Sciences
Sozinova, Olga [email protected] of Philology, Fundamental and Applied Linguistics, Higher School ofEconomics, Moscow, Russia
van Oostendorp, Marc [email protected] University & Meertens Institute
van Raalte, Marlein [email protected] University
Versace, Stefano [email protected] Planck Institute for Empirical Aesthetics, Department of Language and Liter-ature
Useful information
Getting to Leiden
Leiden is a relatively small city in the west of The Netherlands, between the capitalAmsterdam and The Hague, the Dutch seat of Government. For international visitors, itis easily reached by air, railway and road.
Amsterdam Schiphol Airport is the main international airport of the Netherlands, and amajor air hub in Europe. Taking the train is the best means of getting to Leiden fromthe airport. Trains depart from Schiphol Airport to Leiden every 10 to 15 minutes. Thetrains to Leiden usually depart from tracks 5 or 6. Travelling to Leiden will take about20 minutes. An OV chip card, which you need to travel by public transport in theNetherlands, can be bought at a ticket dispenser (in front of the stairs leading to thetracks) or at the booking office near Schiphol Plaza. A 2nd class ticket costs 5,60 euros;1st class costs 9,50 euros. You can check the train schedule on www.ns.nl.
Getting to the university
The workshop will be held in the Lipsius building, the main building of the Facultyof Humanities of Leiden University. The address is: Cleveringaplaats 1. The Lipsiusbuilding can easily be reached by foot (about 15 minutes) from the main train station ofLeiden.
Accommodation
Hotels are easy to find in Leiden. We listed some hotels and B&B’s that are convenientto the conference venue.
’Walking time’ indicates the time it takes to walk from the hotel to the main conferencevenue (the Lipsius building: Cleveringsplaats 1).
Hotel De Doelen, walking time: 4 mins.
Hotel Nieuw Minerva, walking time: 8 mins.
Ibis Hotel Leiden, walking time: 10 mins.
Best Western City Hotel, walking time: 11 mins.
Goldon Tulip, walking time: 14 mins.
Huys van Leyden - Boutique Hotel, walking time: 17 mins.
Rembrandt Hotel Leiden, walking time: 8 mins.
Hotel Mayflower, walking time: 8 mins.
Residence 102, walking time: 18 mins.
Bed & Beschuit, walking time: 12 mins.
More information can be found on the website of Leiden Visitor Centre.
Access to the Internet
During the conference it will be possible to access the Internet with your laptop, tabletor smart phone. If you have access to Eduroam you can access this network also at our
university. If not, you can log on to our wireless network by using an activation code.As a network you should select ‘Leiden University’. When you open the browser, youwill be directed to a log on page of LUWA or the Quarantaine network. On this pageyou can choose the option: ‘I am a guest with an activation code’ to log on.
You can ask one of the organizers for an activation code.
Visitor Centre Leiden
Address: Stationsweg 41
Phone: 071–5166000
Opening hours:
• Monday/Friday: 7:00 – 19:00
• Saturday: 10:00 – 16:00
• Sunday: 11:00 – 15:00
You can go by the Visitor Centre if you are looking for souvenirs, maps, postcards, giftcards, maps with city walks, information on public transport, etc.
Public transport
Buses
Most buses leave from the bus station in front of Leiden Central Station. If you want toplan your bus trip, you might want to use the website www.9292ov.nl, or the timetablesat the bus station.
Trains
From Leiden Central Station you can take trains in the direction of for instance Amster-dam, Utrecht and The Hague. The website www.ns.nl allows you to plan your trip indetail.
Keep in mind that you will need an OV chip card if you want to use the public transport,which you can buy at the Visitor Centre or at the train station.
Taxi
Taxi Centrale Leiden (TCL)Phone: + 31 71 210 02 10
Taxi WielkensPhone: + 31 71 589 05 03
Evening Shop
Night Market, Breestraat 77
Corner Supermarket, Breestraat 54
Pharmacy
Etos Drogisterij, Donkersteeg 11
Etos Drogisterij, Stationsplein 3H
Restaurants
The city of Leiden hosts many wonderful restaurants. If you feel like going on anadventure, but at the same time you also don’t want to get lost, you can considerwalking through streets like: Kloksteeg, Heresteeg, Nieuwe Rijn, Beestenmarkt, andNoordeinde. In these streets you will find numerous restaurants.
We also made a small selection of some of our favorites. For six restaurants, you willfind the address, opening hours, and an indication of the price of a main course. Have awonderful evening!
• Fresh ‘n Fast (FF), Kloksteeg 7open: 17:00 – 22:00, tel: + 3171 514 1071price range: e10–e15 main course* Nice salads and burgers
• Jacketz, Maarsmansteeg 10open: 12:00 – 22:00, tel: + 31 71 513 5506price range: ± e10 main course* Wonderful baked potatoes
• Oudt Leyden Pancake House, Steenstraat 49open: 10:30 – 21:30, tel: + 31 71 513 3144price range: ± e10 main course* Just have delicious Dutch pancakes in a cozy restaurant
• Restaurant Rembrandt, Nieuwe Beestenmarkt 10open: 17:00 – 22:00, tel: + 31 71 514 4233price range: e15–e20 main course* Eat and check out some paintings by Rembrandt
• De la Soul, Morsstraat 60open: 17:30 – 22:00 (Mo. closed) , tel: +3171512 5671price range: ± e10 per course* Enjoy the music, and have some soul food
• Verboden Toegang (Eng: Forbidden to Access), Kaiserstraat 7open: 18:00, tel: + 31 71 514 3388price range: e15 – e20 main course* Do you feel like doing something that is not allowed? Take the easy way, andhave a delicious meal here.
Abstracts
(in alphabetical order by first author’s last name)
Jean-Louis AROUIParis-8 University, UMR 7023 “Structures Formelles du Langage”
A TEMPLATE FOR A CLASSICAL ARABIC METER: THE KAMIL
This paper proposes a new template for the kamil-1, a classical Arabic meter usedbetween 450 and 670 of the Christian era.The line quoted in (1), credited to al-Aḫṭal (Paoli 2008 : 170) is an example of thismeter:
(1) wa- ’idā aṣ ḥawtu fa-mā ’uqa iru ṣṣ ‘an nadan L L H L H /L L H L H /L L H L H /
wa-kamā ‘alimti šamā’ilī wa-takarrumī L L H L H /L L H L H /L L H L H
Because of the results of an extensive research in empirical metrics (Paoli 2008) it isknown that the kamil-1 may have the following moraic and syllabic forms:
(2) Kāmil-1 in ancient Arabic poetry1
Moraic formμμ μμ μ μμ μμ μμ μ μμ μμ μμ μ μμ μμ μμ μ μμ μμ μμ μ μμ μμ μμ μ μμ
LL H L H LL H L H LL H L H LL H L H LL H L H LL H L H
H H H H H H
Syllabic form
It is generally admited that the metrical positions and feet run as follows:
(3) Metrical positions and feet in the kamil-1 (traditional analysis)
1a1b 23 4 5a5b 6 7 8 9a9b 10
11 12 13a13b 1415 16 17a17b 18
19 20 21a21b 2223 24
1 5 9 13 17 21
1. In each foot, the opening metrical position may be freely LL or H. LL is theunmarked form, and to get H, we need contraction, which is called iḍmār in Arabic.
2. In Arabic traditional metrics, the stable part of a foot is called a watid. A watiddoes not accept any variation in its prosodic form (except sometimes at the end of acolon, see Paoli 2008: 105). In the kamil-1, the stable part of a foot stands in the lastthree metrical positions. Nevertheless, the xalilian theory of Arabic meters considersthe watid of a kamil-1’s foot to rely on the third and fourth metrical position only.
In this paper, I propose a template for the kamil-1. In this template, the metricalconstituent usually understtod as a foot is described as a metron:
1 Paoli (2008: 170, 176).
Aroui
(4) Metrical template for the kamil-1Metra I II III IV V VI
Feet W S W S W S W S W S W S
Metrical positions W S W S W S W S W S W S W S W S W S W S W S W S
Subpositions 1 2 3 4 5 6 7 8 9 10 11 12
This template works with the following correspondence rules:
(5) Correspondence rules for the kamil-11. A strong foot is made of invariable metrical positions.2. In a weak foot, a strong metrical position is invariable, and a weak
metrical position is preferably made of two subpositions. Failing that, thesubpositions can be omitted.
3. A strong metrical position is associated with a heavy syllable.4. A weak metrical position is associated with a light syllable when it
belongs to a strong foot. In a weak foot, it is preferably divided into twosubpositions and each subposition is associated to a light syllable; failingthat, the weak metrical position is associated to a heavy syllable(contraction (iḍmār)).
(4) and (5) have the following advantages: they can explain the watid of xalilianmetrics: the watid fits with the strong feet.With (4) and (5), it is also easy to explain why the contraction applies for some metricalpositions and does not apply for others: only a weak position belonging to a weak footmay be subject to a contraction.
ReferencesBOHAS, Georges & Bruno PAOLI (1993): Métrique arabe: une alternative au modèle
xalîlien. Langue française, 99, pp. 97-106.― (1997): Aspects formels de la poésie arabe. 1. La métrique classique. Toulouse:
AMAM.PAOLI, Bruno (2008): De la théorie à l’usage. Essai de reconstitution du système de la
métrique arabe ancienne. Damascus: Institut Français du Proche-Orient.― (2009): Generative Linguistics and Arabic Metrics. In J.-L. Aroui & A. Arleo (eds.),
Towards a Typology of Poetic Forms. From Language to Metrics and Beyond.Amsterdam: Benmùains (‘Language Faculty and Beyond’, 2), pp. 193-207.
Aroui
Romain BENINI
UMR 5611 LIRE / Paris III – Sorbonne Nouvelle
The metrical ambivalence of lines in 19th
century French songs
Abstract
Musical meters and those of French literary poetry do not share the same
structures and do not rely on the same units. In songs however, the linguistic material is
designed to match musical structure. Singing presupposes employing a musical meter,
but song lyrics do not necessarily have an inherent metrical structure (i.e. a metrical
structure independent of that of the tune). In this talk, I propose to describe certain
features of lines found in the lyrics of 19th century French songs. The corpus under
scrutiny is a collection of 607 songs written on preexistent tunes and published in Paris
between 1848 and 1851.
The lyrics of these songs reveal a clear concern for the conventions of classical
versification, as indicated by the typographical layout (lines and paragraphs) and by the
observance of several graphic or non graphic rules that govern classical literary verse
(hiatus, word-final consonants, dieresis). Nevertheless, the texts’ metrical structure
cannot be entirely explained by invoking traditional constraints on French literary
poetry, and several features suggest a metrical structure that cannot be characterized in
purely textual terms.
The first point we will discuss is a difference between refrains and verses in the
way line lengths are patterned. In French literary verse, metrical regularity is based on
syllable count equivalences. To be metrical, a line must have the same number of
syllables as a line that precedes or follows it, or that is located at the same structural
place in an analogous group of lines found in the same periodical sequence. Yet song
refrains often do not show such contextual equality. This difference between refrains
and verses can be explained by assuming that in refrains it is musical structure that is
prevalent. Refrains are repetitions both musically and textually. Verses, by contrast,
have lyrics that vary across stanzas. This fundamental difference leads to a clearer
grammatical structure for the lyrics of verses.
A second point concerns the grouping of lines into stanzas, which is done in
French by rhyming. In classical literary poetry, rhyming groups lines into saturated
systems, i.e. systems where each line matches with at least one other line that rhymes
with it. Lines in stanzas are also subject to a morpholexical constraint of uniqueness
(non repetition). These constraints are not strictly observed in the songs of our corpus,
where some structures like AbAa can be found. AbAa violates non-repetition and it is
not saturated because b lacks a matching line (analogous structures are common in
French music; B. de Cornulier calls them rabéraa). However, several songs enforce
saturation by employing AbbAa sequences. The musical sheets suggest that this
adaptation works like a trompe-l’œil, since the posttonic parts of the lines bb can differ
when sung. This could be an argument to postulate the possibility of a metrical
ambivalence in songs lyrics, some sequences being used as two lines in the text but only
one group in singing.
Benini
Metricalizer³ - Automated Metrical Analysis for German Language
Klemens Bobenhausen, Benjamin Hammerichwww.metricalizer.de
Abstract
Metricalizer³ (M³) is tool for analysing the metrical structure of German verse. Its rule based al-gorithm structure enables it to handle all input nevertheless if words are lexically accepted or not.M³ analyses verse for various metrical structure components like prosody, meter and rhyme. M³ is able to compute the prosody of normal discourse making it possible to compare the two layers “Prosody” and “Meter” on an abstract basis and thus evaluate positions of “Metrical Complexity”. This information is used to compute the “metricality” of the text, i.e. if the text is metrically bound or unbound. These techniques enable the M³ to compute a typological classification of any given poem.
The next goal of the project is to build up a large corpus of automatically marked German verse.This will enable users and scientists to evaluate the overall picture of the development of German poetry in the last centuries and can give answers to detailed questions like “Which meter does Goethe use the most between 1800 and 1810?” or “Which kind of metrical complexity is used by which author?” or “Which rhymes are used the most between 1750 and 1800?”. M³ is tested and accessible for free for anyone interesting via a web interface at www.metricalizer.de. At the Work-shop you will have the opportunity to test the newest interface and give us feedback.
References
Bernhart A. W. (1974), “Complexity and Metricality”, Poetics 12, 113-141.Bobenhausen K. (2011), “The Metricalizer – Automated Metrical Markup of German Poetry”, Littera. Studies in Language and Literature 2, 119-131.Halle M. & Keyser S. M. (1971), English Stress, Its Form, Its Growth, and Its Role in Verse, New York: Harper and Row.Küper Ch. (1988), Sprache und Metrum. Semiotik und Linguistik des Verses, Tübingen: Niemeyer Verlag.Schmidt S. A. & Barsch A. (1981), Generative Phonologie und Generative Metrik. Rekonstruktive Untersuchungen auf der Grenze zwischen Linguistik und Literaturwissenschaft, Opladen: Westdeutscher Verlag.
Bobenhausen & Hammerich
Svetlana Bochaver (Institute of Linguistics, Russian Academy of Sciences,
Dmitri Sitchinava (Institute of the Russian Language, Russian Academy of Sciences,
The Spanish Verse Corpus
The Spanish Verse Corpus is presently being built at the Institute of Linguistics, RAS. Several
Spanish corpora created by the Spanish Royal Academy of Sciences do include some poetic
texts. However, the amount of these texts within the existing corpora is rather small. Moreover,
none of these corpora has the option to search only within the poetic texts. Neither have they a
separate annotation for verse (meter, stress rhythm, rhyme, stanza parameters etc.).
The present project is aimed at creating a tool for exploring both the linguistic characteristics and
the metrics of the Spanish-language poetry. The team uses the experience of the linguists and
programmers that have created such resources as the Russian poetic corpus
(http://ruscorpora.ru/search-poetic.html) and the Bashkir poetic corpus (http://web-
corpora.net/bashcorpus/search/index.php?interface_language=en). Both corpora are available
online and searchable by linguistic and metric parameters. See also (Liberman 2013) for a
general layout of poetic corpora.
The SVC initially encompasses poetic texts, both classical and modern ones, written in Spain.
Later it will include also the Latin American poetry. The team uses the texts included into the
anthology (Rico 2011) and the series Clásicos Castalia that provides a representative collection
of the Spanish poetry belonging to different chronological periods and literary movements.
Each text is annotated by date, genre, linguistic parameters (POS annotation, grammar
categories, syntax), and verse parameters (meter, rhyme types, stanza structure). The (classical)
Spanish versification is based on syllable count, but at the same time, different tendencies
concerning the place of stressed syllables within a line can be discerned for different historical
periods (cf. Gasparov 2006). Each line is annotated by its rhythm. The annotation is based on the
descriptions of the Spanish verse and metrics (Navarro Tomás 1991), (Quiles 1975),
(Domínguez Caparrós 1975). The texts are annotated using the algorithms defining the place of
stressed syllables and elisions; the results are checked manually. The corpus is in a XML-based
format with tags on different levels (word, line, stanza, text). Some effects of interaction between
the levels and difficult issues concerning the annotating process will be discussed.
The first results of annotating the Renaissance texts (15-16th
centuries) will be presented at the
workshop.
References
Domínguez Caparrós, J.: 1975. Diccionario de métrica española, Madrid, Alianza editorial.
Gasparov, M.: 2006. A history of European versification. Oxford: Clarendon Press.
Liberman, M.: 2013. Design of a corpus of scanned verse. From M@90, Metrical Structure:
Stress, Meter and Textsetting, to celebrate Morris Halle's 90th birthday, a 2-day workshop held
at The Department of Linguistics and Philosophy of the Massachusetts Institute of Technology
on September 20 and 21, 2013. (https://www.youtube.com/watch?v=k7abJPM9L3o)
Bochaver & Sitchinava
Navarro Tomás, T.: 1991, Métrica española, Barcelona, Editorial Labor.
Quilis, A.: 1975, Métrica española, Madrid, Ediciones Alcalá.
Rico, F.: 2011, Mil años de la poesñia española. Antología comentada con la colaboración de
José María Micó y Guillermo Serés y de Miguel Requena y Juan Rodríguez, Barcelona,
BlackList.
Bochaver & Sitchinava
The genetics of oral texts. Empirical findings and ethnographic investigation in the field of Sardinian improvised poetry
Paolo Bravi
Introduction In this paper proposal I describe an experiment carried out with the collaboration of three Sardinian improvising poets whose aim was to investigate the process of creation of a very complex metrical form, known as mutetu longu, during a poetic contest (Zedda, 2009; Bravi, 2010). The study inserts itself into the broad field of the “genetic criticism” of texts, which has a long history and is extensively practiced as regards written texts (Hay, 1979; Deppman, Ferrer, & Groden, 2004). Its originality lies in the fact that it represents an attempt to examine, through both empirical and ethnographic data, the genetic of an oral text, in particular seeking to investigate how a poem is created, in a short stretch of time, during an improvised poetical duel.
Figure 1. The poet Paolo Zedda recorded through an headset microphone during the
phase preceding its turn.
Experiment – A poetic contest was organized thanks to the collaboration of three semiprofessional improvisers from Sinnai (Sardinia), in the private home of one of the three poets. The poetic contest was audio and video recorded using a particular method of audio recording which relied on the active cooperation of the poets, who had been informed from the very start about the aims of the experiment. Audio recordings were made using microphone headsets which the poets were asked to wear before one turn and another, when the poets were not actively performing their poems. They were asked (and sometimes reminded during the experiment) to speak their thought processes aloud (though in a low voice), so that the progressive creation of the mutetu, as well as any “comments” about the contest, could be recorded through the headset microphone (Figure 1). In actual fact, this is something that, to a certain extent, poets actually do of their own accord during poetry contests. Indeed, you can quite often see the poets talking or humming to themselves – sometimes covering their mouths with their hands – while they are sitting down waiting for their turn.
Figure 2. An example graph describing the elaboration and repetition of lines during the creation and memorization of a mutetu longu.
The goal of the experiment was clearly not an attempt to literally “transcribe” in an explicit verbal form the entire spectrum of thought processes which the poets put to use during the phase of elaboration, but is far more limited and less ambitious. It is an attempt to use the indications and clues given by the poets – albeit often not in a constant and coherent manner – to reconstruct aspects which could possibly throw some light on the way that this creative activity is carried out. At the same time, the experiment actually provided objective elements to inspire discussions of the topic with the protagonists (the poets), and allowed the partial reconstruction of the strategies used in the creation and memorization of the mutetu, its timing and the order in which the verses are created, etc.In fact, as regards Campidanese improvised poetry, the improviser poet does not create the verses almost “off the cuff”, as happens in the case of other systems of improvisation (e.g., the one in octaves), but rather, he elaborates the framework of the mutetu while the other competing poets are taking their turn. In this particular case, seeing that there were three poets taking part and that each intervention lasted around four minutes, each poet had about seven /eight minutes to develop his ideas, even though he was also listening to the other poets’ propositions regarding the chosen topic. Different kinds of graphs were drawn up for each mutetu, showing the progressive elaboration over time of the creation of the mutetu longu and its memorization (see example in Figure 2).
Conclusions – Data obtained through the experiment were confronted with the personal statements given by the poets. Generally speaking, the three poets exhibit some common traits and follow the same overall path for the creation and
Bravi
memorization of the mutetu longu, but they also show characteristics which appear to be idiosyncratic and which distinguish each poet’s personal approach to the invention of the poems.
Bravi
Bibliography
Bravi, P. (2010). A sa moda campidanesa. Pratiche, poetiche e voci degli improvvisatori nella Sardegna meridionale. Nuoro: ISRE.Deppman, J., Ferrer, D., & Groden, M. (A cura di). (2004). Genetic Criticism. Texts and Avanttextes. Philadelphia: University of Pennsylvania Press.Hay, L. (1979). La critique génétique: origines et perspectives . In AA. VV., Essais de critique génétique (p. 227236). Paris: Flammarion.Zedda, P. (2009). The Southern Sardinian Tradition of the Mutetu Longu: A Functional Analysis. Oral Tradition , 24 (1), 340.
Bravi
The Rhyme Analyzer toolkit, and its use in analysis of lyrics and poetry
Daniel G. Brown ([email protected]) David R. Cheriton School of Computer Science, University of Waterloo, Canada
Abstract:
In 2009, we developed the Rhyme Analyzer [1,2,3], which automatically detects rhyme features in poetry and lyrics. Because our initial domain was the lyrics of rap music, where complexity of rhyme is one of the defining features of the genre, the Rhyme Analyzer detects complicated rhyme features, such as imperfect rhyme, internal rhyme, nested rhyme and so on. The software is based on probabilistic methods in sequence alignment that are used in analysis of biological sequences such as DNA, but its use is straightforward for non-‐expert practitioners.
The Rhyme Analyzer also identifies meter and rhythm of lyrics or poetry, and in particular can identify words for which the stress pattern implied by the meter of a poem does not match the prosody of the word [4]; this again is a common form of wordplay in rap music.
Because of its efficiency, the software can be used to automatically annotate rhyme and meter in the entire oeuvre of a performer or poet, which allows us to characterize the types of wordplay and rhyme made by that artist; examples of the features that result are the average number of internal rhymes per line that a lyricist creates, or the length in syllables of an average rhyme. These features enable quite a bit of surprising textual analysis.
For example, with rap music, we are able to show that the genre has increased in complexity of rhyme over the first 25 years of its existence, and we can identify examples of ghost-‐written songs (where the performer is not the rap’s creator). We can identify the creator of a query song, out of a set of 25 performers, with over 50% accuracy. We can separate “old-‐school” and “new-‐school” rap, and we can confirm cases where artists are trying to perform “in the style of” other performers [3, 4].
In recent work, we are trying to see how much high-‐level features like those derived from lyrics can be predictive of success of popular music songs. In a preliminary study [5,6], we have shown that songs with more complex rhyme are more likely to be hits, while flops disproportionately have simpler rhyme. (This finding likely comes because complexity in lyrics is suggestive of high craftsmanship in the entire songwriting process, but there are few ways for a computer algorithm to identify craftsmanship from a digital recording.)
We would like to start applying the Rhyme Analyzer to large-‐scale analysis of poetry, and are very interested in how the program’s behaviour can be applied to large-‐scale poetry corpora.
Brown
References:
1. H. Hirjee, D.G. Brown. Automatic detection of internal and imperfect rhymes in rap music lyrics. Proceedings of International Symposium on Music Information Retrieval (ISMIR) 2009, 711-‐716.
2. H. Hirjee, D.G. Brown. Rhyme Analyzer: An analysis tool for rap lyrics. Late-‐breaking demo at ISMIR 2010.
3. H. Hirjee, D.G. Brown. Using automated rhyme detection to characterize rhyming style in rap music. Empirical Musicology Review 5(4): 121-‐145, 2011.
4. H. Hirjee. Rhyme, rhythm, and rhubarb: using probabilistic methods to analyze hip hop, poetry, and misheard Lyrics. MMath thesis, University of Waterloo, 2010.
5. A. Singhi, D.G. Brown. Hit song detection using lyrics features alone. Late-‐breakind demo at ISMIR 2014.
6. A. Singhi, D.G. Brown. Can song lyrics predict hits? In review.
Brown
Using MARY text-to-speech to determine Rhythm andMetre in English Poetry
Michael Cade-Stewart1
1Department of Digital Humanities, King’s College London
Abstract
Introducing results of my research in automatically determining the metre and rhythmof verse using the ”MARY” text-to-speech software. My approach is to extract andanalyse data from intermediate stages of MARY’s natural language processing, in orderto predict where some of the beats will fall when the poem is performed or read. Rulesand penalties for promotion and demotion of syllables then attempt a scansion of thepoem and output the best result. My method can determine the metre and ”foot-type”of Yeats’s poetry with a high degree of accuracy, and can do so same for Tennyson’spoetry with even more success.
Cade-Stewart
A moraic analysis of the Old English metrical line This talk presents an analysis of the metrical structure of Old English verse. Its purpose is to express the metrical system of OE verse in a way which is compatible with syntactic analysis. A selected, varied corpus of over 5000 lines from a variety of verse texts was analysed for syllabic structure, vowel quantity, stress distribution and alliteration. Simple descriptive statistics were used to identify typical features and their distribution. Golston & Riad’s (2003) generalisation that OE lines contain between 8 and 16 vocalic moras was confirmed for the corpus, to the same level of accuracy. Statistical analysis showed the moraic length of these lines is normally distributed around 12. To explain this, the asymmetric Germanic foot proposed by Dresher & Lahiri (1991) was adapted to account for typical verse foot (Vft) structure. The metre thus arises from the phonology of the language, by way of the prosodic hierarchy. It is shown that the text is organised to fit four verse feet, which are composed of two metrical positions (Φ), the left position is by default two moras (μμ), but can be reduced to one, and the right position is by default one mora (μ-), but can be increased to two, depending on lexical input. A prototypical line is shown in Fig. 1. 1. line Intonation Phrase on-verse off-verse Prosodic Phrase Vft Vft Vft Vft Prosodic Word Φ Φ Φ Φ Φ Φ Φ Φ Prosodic Foot (μ μ μ-) (μ μ μ-)(μμ μ-)(μμ μ-) Total=12 moras Abraham wunode ēðel…ēardum “Abraham dwelt in his native land” Genesis l.1945 Figure 1. A metrical tree-diagram of prosodic structure in OE verse. Minimal (example 2) and maximal (3) lines are each produced by four violations of the constraints which produce the 3-mora feet, making them equally infrequent. Note that the inflexibility of minimal and maximal lines causes syntactic boundaries to mismatch with foot boundaries. The caesura is considered a syntactic rather than a metrical boundary, as in (3). 2. (μ- μ-) (μ- μ-) (μ- μ-)(μ- μ-) nergend usser com nihtes self “…our saviour. He came that very night…” Genesis l.2634 3. (μμ μμ) (μ μμ μ) (μ μμ μ) (μμ μμ) ðǣr hīe æt swǣsendum sǣton bū tū, “…where they at mealtimes sat together…”
Genesis l.2780 The Vft can be identified by a stressed syllable, usually but not necessarily on the left (pace Getty (2003)). Typical stress/unstress patterns (as in Sievers 1893) can be shown to be emergent structures, determined by left-headedness constraints at all levels of the line, which interact with the phonology of the chosen lexical items and syntactic structures. This framework provides a quantitative, one-size-fits-all metre for all standard lines of OE verse.
Cooper
References Dresher, B.E. & Lahiri, A. 1991. “The Germanic Foot: Metrical coherence in Germanic.” Linguistic Inquiry Vol.22.2, 251-286. Getty, Michael. 2002. The Metre of Beowulf: A Constraint-Based Approach. Berlin: Mouton de Gruyter. Golston, Chris. & Tomas Riad. 2003. “Scansion and Alliteration in Beowulf”. Jahrbuch für internationale Germanistik 35: 77-105. Sievers, Eduard. 1893. Altgermanische Metrik. Halle: Max Niemeyer.
Cooper
A repository of verse templates
Varun. deCastro-Arrazola1,2
1Leiden University, 2Meertens Institute
Abstract
All known languages make use of a number of templates in order to create new songsand poems. The purpose of the database is to store and document them in a systematicway. In this talk I describe its design structure and propose an expert-sourced model topopulate it.
Poetic templates have long been compiled in written form for several European lan-guages. During the last couple of decades, digital versions of this kind of material havebeen created (e.g. BedT, ReMetCa). For typological research, a shortcoming of theseprojects tends to be their lack of a common ontology.
At least two projects have attempted a typological survey of the world’s verse traditions.These projects encode a number of features about individual songs (Cantometrics, Lomax& Grauer 1968) or verse forms (VerseTyp, 2011). Despite their virtues, many typologicalquestions need a finergrained explicit representation of the constituent structure ofthe templates. In principle, the database presented here and one such as VerseTypboth describe the same objects (templates) but at different levels of detail, being thuscomplementary.
The main components of the database are the following.
• Template list: each well-documented template gets an ID.• Template features: e.g. the language it uses, the period when it’s actively em-
ployed, links to related templates.• Sources: templates are described in scholarly publications and/or are instantiated
in corpora of poetic or musical texts.• Constituent structure: e.g. a stanza, with two couplets, 8 positions in each line, 4
bars in each phrase.• Constituent features: e.g. relative prominence, a linguistic boundary, a contrastive
timbre or harmonic function, a scale degree. Constituents can also belong toidentity sets, such as rhyme, alliteration or repetition.
The systematic encoding of templates enables addressing typological or smaller-scalequestions in a consistent way. How many sub-constituents do constituents generallyhave? How far apart can identity relations be? The repository also provides centralisedbibliographical information for the verse structures used in the world’s languages.
References
Fabb, N. & Versace, S. 2011. “A database as a method of raising typological questionsabout poetic form”. In: Austin, P., Bond, O., Nathan, D., & Marten, L. (eds.), Proceedingsof conference on language documentation & linguistic theory 3, pp: 289–296.
Lomax, A. & Grauer, V. 1968. “The Cantometric Coding Book”. In: Folk song style andculture, pp: 34–74. American Association for the Advancement of Science.
deCastro-Arrazola
Rig-Vedic metrics: A constraint-based approach
Kristen de Joseph
Leiden University
Over a century since their publication, Edward Arnold's Vedic metre in its historical development
(1905) and Hermann Oldenberg's Metrische und textgeschichtliche Prolegomena zu einer kritischen
Rigveda-Ausgabe (1888) remain the standard handbooks on Vedic meter to this day. While these
works remain valuable compendia of the empirical facts of Rig-Vedic (RV) meter, the state of the
art of prosody and metrics has evolved considerably in the past hundred-plus years; the study of RV
meter merits an update that incorporates these advances. In this talk, I will present a constraint-
based analysis of Vedic meter, one that respects the traditional wisdom but is also firmly rooted in
the present-day science of metrics – particularly as it has taken shape in the past 20 years, as
constraint-based metrics (Golston & Riad 1997, 2000, 2005; Hayes 2011, 2012) have allowed for an
unprecedented depth of metrical analysis. In line with these approaches, I presuppose that Vedic
meter is not just an arbitrary construct, but proceeds naturally from the innate features of Vedic
prosody; thus we can see not only how Vedic meter operates, but also why it selects certain metrical
constants and favors certain tendencies over others within the context of its overall prosodic system.
At the same time, the stylized prosody of formal poetry offers a prospectus of the major features of
its native prosodic system – a convenient state of affairs for the earliest Vedic, for which poetry
furnishes our sole testimony. In the best-case scenario, these recent approaches – which have
fruitfully yielded new perspectives on many other world poetic traditions – can allow us to retrace
the system that existed in the minds of the poets, and how it proceeded from their own linguistic
competence: a window into a mental reality that would otherwise remain irrecoverable.
References
Arnold, E. V. (1905). Vedic metre in its historical development. Cambridge: Cambridge University
Press.
Golston, C. & Riad, T. (2000). The phonology of Classical Greek meter. Journal of Linguistics, 38,
99–167.
———. (2005). The phonology of Greek lyric meter. Journal of Linguistics, 41, 77–115.
Hanson, K. & Kiparsky, P. (1996). A parametric theory of poetic meter. Language, 72, 287–335.
Hayes, B. & Moore-Cantwell, C.. (2011). Gerard Manley Hopkins's Sprung Rhythm: Corpus study
and stochastic grammar. Phonology, 28, 235–282.
Hayes, B., Wilson, C. & Shisko, A. (2012). Maxent grammars for the metrics of Shakespeare and
Milton. Language, 88, 691–731.
de Joseph
Oldenberg, H. (1888). Die Hymnen des Ṛgveda, I: Metrische und textgeschichtliche Prolegomena.
Berlin: Verlag von Wilhelm Hertz.
de Joseph
François Dell
Centre de Recherches Linguistiques sur l’Asie Orientale (CRLAO)
CNRS / EHESS, Paris
For the session Encoding and decoding verse.
Title: Meters, performance templates, and their interactions.
Fabb 1997: 94 draws a distinction between “meter” and “performance template”. A meter specifies
the conditions that a stretch of text must meet if it is to count as a well-formed line of verse of a certain
type. Meters do not specify how texts are to be performed. Performance templates, on the other hand,
do precisely that. In Fabb’s terms, the melodies of songs are performance templates. I will first outline
a typology of performance templates, based on the extent to which they control pitch and timing.
Most performance templates impose restrictions on the texts that satisfy them. In some cases these
restrictions are quite similar to the kinds of restrictions imposed by meters. In the second part of the talk
I will review the main issues involved in devising a framework that would enable us to subsume meters
and performance templates under the same set of principles and representations, and to analyze their
interactions.
Fabb, Nigel (1997) Linguistics and literature. Oxford: Blackwell.
Dell
Nigel Fabb: The metrical line in working memory
Working memory is able to contain about four chunks of verbal material at any time (equivalent to about fifteen words of connected prose).
I begin by reviewing earlier proposals (e.g., Tsur, Hogan, Willett) that the line fits as a whole unit into working memory, along with the related proposal ‐ which I dismiss ‐ of Turner and Pöppel that the line fits as a whole unit into the time‐limited capacity of auditory working memory (now known as the phonological loop). These proposals generally underestimate the capacity of working memory, and thus must sometimes divide longer lines into memory‐specific sub‐units. This underestimation is strongly influenced by Miller’s famous formulation of a capacity of seven plus or minus two, which Cowan (2000) suggests was ‘probably a rhetorical device’ and that it has long been clear that the capacity limit is more like ‘four plus or minus one’ but with four being four chunks, each capable of holding sub‐units, an observation basic to the model of working memory formulated by Baddeley and Hitch (1974). Thus working memory capacity is larger than originally assumed, and can probably hold all lengths of metrical line, and often whole couplets.
I show that it is true for all metrical traditions that the line or sometimes the couplet can in principle fit as a whole unit into the episodic buffer of working memory (in the Baddeley‐Hitch model, e.g., Baddeley 2012). The line is not subject to any limit on auditory or rehearsal duration, and so is not designed to fit into the phonological loop component of working memory. Furthermore, we can formulate a more extensive generalization.
A poem is a text made of language, divided into sections which are not determined by syntactic or prosodic structure.
From this definition, we formulate a generalization.
A poetic section on which systematic added forms depend must be able to fit as a whole unit into the episodic buffer in working memory.
The systematic added forms are metre, rhyme, alliteration and parallelism. The section on which they normally depend is the line, sometimes the couplet. This implies that the added forms of poetry are computed in working memory.
In the final part of this paper, I consider the relation between working memory and long term memory as it applies to the metrical line. A current view (D'Esposito and Postle 2015) is that working memory is a focused attention on elements in long term memory (i.e., rather than two kinds of memory being differently located like RAM and hard drive storage in a computer). The idea that the line is ‘attended to’ has been important for other authors (e.g., Boyd) who have focused on the line in working memory. Knowledge of added form is stored in long term memory and deployed line‐by‐line; an understanding of the aesthetic functions of form, and how expertise in form contributes to aesthetic pleasure may relate to the line being processed as a whole unit in working memory. I also consider Huron’s (2006) proposal that memory is prospective: form is anticipated and Huron argues is subject to a ‘prediction response’, which is perhaps deployed over the line as a unit in working memory.
Fabb
Baddeley, A.D. and G.J. Hitch 1974. ‘Working memory’, in G A Bower (ed.) The Psychology of Learning and Motivation: Advances in Research and Theory New York: Academic pp.47‐89
Baddeley, Alan 2012. ‘Working memory: theories, models, and controversies’, Annu. Rev. Psychol. 63: 1–29.
Cowan, Nelson 2000. ‘The magical number 4 in short‐term memory: A reconsideration of mental storage capacity’, Behavioral and Brain Sciences, 24: 87–185.
Huron, David (2006). Sweet anticipation: Music and the psychology of expectation. Cambridge, MA: MIT Press.
D'Esposito, Mark and Bradley R. Postle 2015. ‘The Cognitive Neuroscience of Working Memory’, Annual Review of Psychology, 2015, Vol.66, p.115‐142
Fabb
Working on the Automatic Scansion of Verse
Pablo Gervas1
1Facultad de Informatica, Universidad Complutense de Madrid
Abstract
As part of an ongoing wider effort to model computationally the literary abilities ofhumans, the NIL research group in Madrid (http://nil.fdi.ucm.es) has for some yearsbeing working on tools for the automatic analysis of the metric structure of poetry. Thishas resulted in the development of a computational solution that for a given poemin Spanish can produce a breakdown into metric syllables and a sequence of stressedpositions. This solution has been used to inform processeses of automatic generation ofSpanish poetry relying on a number of different approaches. This initiative is currentlybeing extended to English, where significant challenges have been found, both in thevery different nature of the language in terms of relationship between written form andphonetics, and in terms of a different metric tradition.
Gervas
Elena González-Blanco Clara I. Martínez Cantón
UNED
ReMetCa and DIREPO Poetry Standardization through a common ontology
ReMetCa: Repertorio Métrico Digital de la Poesía Medieval Castellana (Digital Repertoire on the Metrics of the Medieval Castilian Poetry), www.uned.es/remetca, directed by Elena González BlancoGarcía (UNED, Madrid) is an online, open access metrical repertoire designed for Medieval Castilian poetry. It gathers poetic testimonies from the 12th century (epics, ballads, cuadernavia, etc.) up to the 16th century Castilian Cancioneros. It is a research project, a tool made by and for researchers, most of them, interested in Medieval Literature/verse.
ReMetCa is not presented as just one more metrical repertoire, in the sense that it combines metrical schemes altogether with texts analysis, as well as forms with the main philological aspects that characterize the poems. One of its most important values is that it is a borndigital project designed built on XML standards and conceived to be interoperable with other existing poetry databases and digital repertoires. The Spanish repertoire is conceived as an essential tool to complete the digital European poetic puzzle, enabling users to make powerful searches in many fields at the same time, thanks to the combination between SQL database technologies, XMLTEI markup and the introduction of semantic controlled vocabularies gathered as linked data. We have been working as well in the creation of a general metrical ontology to reflect poetic structures, an issue especially important for two reasons: first, because it is one of the keys of the project to let interoperability among the different traditions, and second, as it means to become extensible and adds more information to enrich its model, it is under constant development.
Gonzalez-Blanco & Martınez Canton
Metrical Tension Revisited
Proposal for Workshop on "The Structure of Verse" "Encoding and decoding verse: structure and perception of metered poetry"
Leiden University 19-20 March, 2014
Halle and Keyser's (1966) original call for a generative standard for metrical description identified two kinds of intuitions poets have about the metrical structure of lines: those about well-formedness and those about tension. For example, a description of the iambic pentameter of Shakespeare's plays should express not only the difference between the set of metrically well-formed lines from Hamlet in (1) and the unmetrical construct in (2), but also the differences among well-formed lines like those in (1) with respect to their tension, or fulfillment of expectations set up by the meter: (1) a. His canon 'gainst self-slaughter. O God! God! b. It is not, nor it cannot come to good. c. But break, my heart, for I must hold my tongue. (2) *His canon 'gainst súicide. O God! God! These latter difference, are crucial to the creation of emotion and meaning through meter -- to the feelings of tumultuous agony in (1a), quiet despair in (1b), and the concern for appearances in (1c). While subsequent research into several major metrical traditions has produced progress if not consensus in modeling intuitions about well-formedness, characterizing intuitions about tension has proved more elusive. In this talk I want to show precisely how the theory of Hanson and Kiparsky (1996) intrinsically formalizes tension. First, its assumption that a meter involves mapping language into a template which is an expression of the rhythmic organization of language defines expectations about constituents, constrasts in prominence, and boundaries. Second, its assumption that a meter's constraints on that mapping involve setting parameters which range over specifically linguistic variables brings into play the markedness hierarchies which figure in rhythmic phonology (Trubetzkoy 1939, Prince and Smolensky 1993, Kager 1999). Insofar as general phonological claims are possible about what types of linguistic constituents are unmarked and marked in particular positions in rhythmic structures (e.g. that light syllables can head feet only if heavy ones can, or that function words can head phonological phrases only if content words can) it is possible can say exactly how all manner of local mappings of language to the template are marked (e.g. the first "God!" of (1a)) and unmarked (e.g. the phrase "But break," in (1c)). Thus, it possible to characterize how local rhythmic choices fully within the bounds of what a particular meter requires may nonetheless feel simple or complex in relation to expectations embodied in the template. In this way, inalienable experiences of fulfilled and unfulfilled rhythmic expectations are encoded in and decoded from the meter, however much interpretation of their purpose and effect may depend on information beyond the meter.
Hanson
Megan E. Hartman
Gnomic Meter in The Wanderer and The Seafarer
In his book Old English Verse, T. A. Shippey argues that in both The Wanderer and The
Seafarer, the gnomic passages at the end of the poemsare the culmination of the wisdom that the
speakers gathers through their earlier trials.1 For this reason, Shippey believes that these poems
could be classified as wisdom verse. Though Shippey focuses on the content of the poems,
wisdom verse can be characterized in other ways as well; for example, Marie
Nelson,CarolyneLarrington, and Paul Cavill argue that the syntax of wisdom verseis quite
distinctive.2
Though it has not been studied as often, gnomic meter can also be distinguished by a
distinctive metrical style.A. J. Bliss describes gnomic verse as some of the most metrically
unusual in Old English poetry,3 andHaruko Momma studies a group of irregular lines singled out
by Bliss in order to argue that they form a special formulaic system, unique to gnomic poetry,
that she terms the “gnomic formula.”4I have looked at the features of gnomic meter particularly
in the hypermetric verse of Maxims I and II and Solomon in Saturnand show that the meter
seems to show many distinctive but interrelated features.5
In this paper, I analyze the metrical features of The Wanderer and The Seafarer,
particularly in the hypermetric sections, to determine how similar they are metrically to
traditional wisdom poetry. This will further allow me to theorize to what degree an audience
might perceive metrical variance in Old English poetry and how the variations can characterize
the content of the poem.
1 T. A. Shippey, Old English Verse, (London: Hutchinson University Library), 1972, 59.
2 Marie Nelson, “„Is‟ and „Ought‟ in the Exeter Book Maxims,” Southern Folklore Quarterly, 45 (1981): 109-121;
CarolyneLarrington, A Store of Common Sense : Gnomic Theme and Style in Old Icelandic and Old English
Wisdom Poetry(Oxford: Clarendon Press), 1993; Cavill, Paul,Maxims in Old English poetry(Cambridge: D. S.
Brewer), 1999. 3See in particular A. J. Bliss, The Meter of Beowulf, revised edn. (Oxford: Blackwell, 1967) and“Single Half Lines
in Old English Poetry.Notes and Queriesn.s 18 (1971): 442-449. 4Haruko Momma, “The 'Gnomic Formula' and someAdditions to Bliss's Old English Metrical System.”Notes and
Queries, n.s. 4 (1989): 423-426. 5 Megan E. Hartman, “Hypermetric Form in Old English Gnomic Poetry,” StudiaMetricaetPoetica 1 (2014): 68-99.
Hartman
XML schema proposal for encoding verse digitally
Petr PlecháčInstitute of Czech Literature, Academy of Sciences of the Czech Republic
Even though XML file format is not really convenient for larger databases due to itsredundancy, it seems suitable for developing standards of verse corpora encoding forvarious reasons:
(1) Unlike relational databases it is human-readable.(2) Unlike relational databases it is flexible in terms of adding new categories and modifying data types.(3) Each XML file that fits the given schema can be easily converted into relational database by means
of one simple script.
The basic tree model where different levels of description are nested, e.g.
<stanza ...> <line ...> <syllable ...> … </syllable> </line>
</stanza>
is however inappropriate in this case, since various elements may overlap. This concernsnot only the obvious relations of versification units (VU) – linguistic units (LU), e.g. line –sentence/phrase, but also VU – VU, e.g. line – stanza:
Upon what cause? // Because my name is George (Shakespeare: Richard III)
as well as LU – LU, e.g. syllable – word:
Puisque tu m'as choisie entre toutes les femmes (Baudelaire: Bénédiction)Кружась в лазурной высоте (Lermontov: Demon).
For these reasons the XML schema proposal that will be presented is based on indexedarray of minimal units (syllables or sounds if needed) while other units form independentelements with range defined in their attributes startOnSyllable and endOnSyllable. e.g.:
<line id="1" startOnSyll="1" endOnSyll="10" text="Now is the winter of our discontent"> <metre id="1" type="iamb" ending="masc" pattern="wSwSwSwSwS"></line>
…
<word id="7" startOnSyll="8" endOnSyll="10" token="discontent" pos="1" sampa="dIsk@ntEnt"/>
Such elements as well as their attributes (apart from those defining range) are optional(but should be unified) so it can cover different types of languages and different systemsof versification.
Plechac & deCastro-Arrazola
Meter as improvement In this talk, Iexplore the hypothesis that meter is derived directly from linguistic grammar, conceived of as a set of ranked constraints (OT, Prince & Smolensky 1993). We identify two general ways in which meter is derived: subversion and improvement. By subversion, some phonological constraint is distinctivelyviolated (Golston & Riad 2000, 2005). This means that markedness is regularly required in some meter. By improvment, some phonological constraint is obeyed to a higher degree in meter than in the regularprosody. The focus of this talkis on improvement. The metrical structure is takento be a (largely) unmarked variantof the prosodic hierarchy of the language. In this view,meter is the same type of object as prosodic morphemes (e.g. reduplicants, nicknames, which are often prosodic syllables, feet or words), butconstituted by a higher category of the prosodic hierarchy. Thefull meter is, then, the same object as an intonation phrase, with all dominated prosodic categories contained in it, where the verse foot is the same object as the prosodic word. Meter as improvement happens when some linguistic constraint, which is sometimes violated in the regular prosodic tree, is fully obeyed in the metrical tree. We look first at the Spanish alexandrines ofRubén Darío (1867–1916). Alignment constraints for phrasal prominence in Spanish are dominated by the requirement on association (TBU=stressed syllable), such that not all phrasal prominences can be fully right-aligned in their prosodic phrases (i.e. in words with non-final stress). In the metrical tree, however, they are always right-alignedin the prosodic phrase(the ”half-line”), sometimes forcing extrametrical syllables in meter. This is illustrated below where accent in (a) is perfectly aligned in both prosodic and metrical structure, whereas in (b) there is misalignment in prosody, but not in meter.Prosodic structure is marked above the text line, meter below. Numbers indicate the twelve positions of the alexandrine,T*=nuclear accent’. a. ( ) IPh ( T*)( T*) PrPh
Cuando empecé a crecér, un vago y dulce son De otoño 6 1 2 3 4 5 6 7 8 9 10 11 12 [ T*][ T*] PrPh (halfline)
[ ] IPh (line)
b. ( ) IPh ( T* ) ( T* ) PrPh
Es la mañana má<gica> del encendido tró<pico>Tutecotzimí 35 1 2 3 4 5 6 / 7 8 9 10 11 12 / [ T*] [ T*] PrPh (halfline)
[ ] IPh (line)
Improvement better occurs onALIGN-R(T*, PrPh) (‘every nuclear T* is at the right edge of a PrPh’).Other examples of meter as improvement are found in the Swedish dactylic hexameters of August Strindberg(1849–1912) and Esaias Tegnér (1782–1846), where the crucial constraints concern the alignment of pitch accents (Strindberg), and the avoidance of word-internal clash (Tegnér). Prince, Alan & Paul Smolensky.1993. Optimality theory: Constraint interaction in generative grammar. Ms, Rutgers University and University of Colorado, Boulder. Golston, Chris & Tomas Riad. 2000. The phonology of Classical Greek meter. Linguistics 38, 99–167. Golston, Chris & Tomas Riad. 2005. The phonology of Greek lyric meter. Journal of Linguistics 41, 77–115.
Riad
Expected frequencies in verse
Poets often exhibit significant and systematic but nevertheless non-categorical preferences in their manipulation of linguistic material (e.g. Hayes, Wilson, & Shisko 2012). For example, in most verse traditions, vowel hiatus is avoided, but not altogether forbidden. Tendencies of every degree and kind can be found in every aspect of poetics (weight- or accent-mapping, caesurae, bridges, rhyme, alliteration, etc.). If one wishes to construct an explicit model (grammar) of the systematic aspects of the poet's compositional process, one must demonstrate that such tendencies reflect active preferences on the part of the poet as opposed to mere chance distributions (e.g. Devine & Stephens 1976, 1994). This is the case only if the configurations occur in the corpus at a significantly different rate from that otherwise expected in the language, or, in other words, if O/E (observed over expected) is significantly different from one. In the Rig-Veda, for instance, 6.2% of (underlying) junctures exhibit hiatus. If words were randomly distributed — one crude but simple baseline of expectation — hiatus would be roughly 50% more frequent (centering on 9.2%), a significant difference (χ2 goodness of fit p < .0001).
In most cases, however, more controls are desirable in establishing baselines of expectation. Consider, for instance, the reported preferential avoidance of a light syllable in line-final position of the hexameter (e.g. Allen 1973). For example, only 6.5% of Vergil's hexameters are light-final. But is this significantly fewer than one would expect if Vergil ignored weight in that position? Light-final words are, after all, fairly infrequent in Latin to begin with. An effective baseline here would consider the incidence of word-final lights not across the whole corpus, but rather in just the subset of Latin words that would otherwise be possible at the end of a line of hexameter, i.e., words meeting certain metrical, syntactic, etc. conditions.
This talk discusses the three approaches to baselines of expectation employed by corpus metrists, drawing on large corpora from several languages (Sanskrit, Tocharian, Tamil, Finnish, Latin, Greek, and Old Norse) and taking note of issues in corpus construction. The first approach is prose comparison (e.g. Tarlinskaja & Teterina 1974, Tarlinskaja 1976, Biggs 1996, Ryan 2011, Hayes & Moore-Cantwell 2011). Consider, for instance, the question of whether accent and/or weight are regulated in Tocharian verse, which is traditionally viewed as syllable-counting only. Using prose extracts controlled in various ways to be verse-eligible, Christoph Bross, Dieter Gunkel, and I argue that Tocharian B verse is preferentially trochaic in the cadence, both quantitatively and accentually.
The second approach, sometimes used when contemporary prose is unavailable or infelicitous for some reason, relies on constructed comparanda or scrambles. For example, Gunkel & Ryan (2011) use "swappable bigrams" (adjacent words in which the reverse order would yield the same weight template, e.g. devān víśvān ~ víśvān devān) to show that the Rig-Vedic poets used word order to avoid certain junctures. Construction can also be applied at the level of the whole corpus (as with Gunkel & Ryan's "Rigged Veda") to test for tendencies such as the presence of a weak caesura in the Vedic dimeter. In this case, a fake dimeter corpus is constructed matching various properties of the original corpus (lexical frequencies, weight and accent distribution, pro- or enclitic tendencies) while leaving word boundaries crucially uncontrolled to test for a difference vis-à-vis the real corpus.
Finally, the third approach relies on statistical modeling rather than on prose extracts or constructed comparanda. In my work on gradient weight-mapping in meter, for instance, I have employed regression models with both fixed and random effects to factor out possible confounds influencing the distribution of interest (Ryan 2011, 2014). I briefly illustrate how such models can be applied to metrical tendencies in general and translated into probabilistic models of grammar such as maxent Harmonic Grammar (as in Hayes, Wilson, & Shisko 2012).
Ryan
Tetiana Shkurko
Donbass National Academy of Building and Architecture (Foreign Languages
Department), Ukraine
ENGLISH VERS LIBRE PROSODY (AUDITORY ANALYSIS RESULTS)
The main feature of poetic speech was defined as the regular occurrence of
phonetic representations (syllable, syllable combination, vowel and consonant sound
represantations) [Polivanov, 1963]. The elimination of traditional verse properties
(meter, rhyme, etc.), the absence of typically verse “prompts” (inversions, repetitions)
in some vers libre varieties on lexical and syntactic levels make this versification
close to prose. Our hypothesis is that vers libre is constituted with a range of definite
stable prosodic features owing to which it is attributed to versification and at the
same time it is perceived as something different from a metered text and prose
The auditory analysis has been performed to research vers libre prosodic features.
The material under analysis includes four vers libre types [Zhovtis, 1974]: an
irregular type (without any repeated items prevailed), a regular type (with partial
prevalence of some repeated items), ‘prosovik’1,2 (1 – encoding verse lines is made
due to clearly marked rhythmic invariable, i.e. overemphasis on the last word in
every line; 2 – the type is characterized by intonation lack of lines finality in case of
carrying over words). Some prosaic extracts have been analyzed to compare them
with vers libre. Besides, vers libre has been written as a piece of prose (quazi-prose)
and reproduced orally. The prose has been presented as vers libre in two different
graphic representations (quazi-verse) and cited as a verse
Summary. All vers libre prosodic features create the poetic form. The most
important verse qualities are presented by the accent system and rhythmical structure
(RS): 1) the presence of strongly accentuated syllable almost in all autosemantic
words; frequent occurrence of strongly stressed functional words resulting in their
prosodic self-dependence and, hence, stress decentralization in most vers libre lines;
2) the tendency to the similar anacruses, the appearance of rhythmic dominant on the
last ictus of a verse line, additional stresses in polysyllabic words due to the
alternating placement of prominence peaks in the speech in English; 3) the presence
of such frequent structures as one-syllable 1/1, two-syllable 2/2, 2/1, three-syllable
3/2, 3/3, four-syllable 4/3; 4) masculine clausula in most vers libre lines; 5) frequent
prominence peaks transfer from the first syllable to the last one in three-syllable RS
at the end of lines and rhythmical uniformity in line cadences.
The difference between vers libre and prose is marked mainly by temporal and
pausal peculiarities.
References:
1. Zhovtis A.L. Problema svobodnogo stikha i evolyutsiya stikhovykh form.
Dissert… doct. filol.nauk. – Alma-Ata. – 1974. – 445 s.
Shkurko
2. Polivanov Y.D. Obshchiy princip vsyakoi poeticheskoi tekhniki // Voprosy
yazykoznaniya. – 1963, 1. – S. 99-112.
Shkurko
Tatyana Skulacheva
Verse and prose: linguistic regularities which differentiate them and their possible influence over
human brain
Rhythm, intonation, syntax and semantics are studied with the help of quantitative and
statistical methods. The focus of the study is on the linguistic regularities of verse structure,
which are present in all types of verse so far studied (Russian, English, French of different
periods, literary trends and individual styles) but are absent from all so far analyzed prosaic texts.
A number of very stable regularities which differentiate verse from prose at different levels of
linguistic structurewill be described. These regularities are interconnected with the main and
most important feature of a verse text – its division into lines, and seem to influence human
consciousness in the similar and most peculiar way.
Results of psychological experiments are described and hypothesis about the influence of
theverse structure over human consciousness is suggested. The future possibilities of linguistic
(phonetics, syntax, semantics) study of verse andphsychological, neurophysiological and even
biochemical study of the influence of verse over human brain will also be described.
Skulacheva Tatyana,
V.V.Vinogradov Institute of Russian Language, Russian Academy of Sciences
Skulacheva
RHYME PROPERTIES IN THE MATERIAL OF MARINA TSVETAEVA
The current research points out the problem of the rhyme patterns in the Russian poetry.
The research is focused on the stressed vowels distribution in the rhymes in the material of Marina
Tsvetaeva, one of the greatest Russian poets of the twentieth century.
Considering the article “On stressed Russian rhyme and non-rhyme words” by Lilly 1987
I put forward two questions: will the distribution of the vowels in the Marina Tsvetaeva’s poems
be the same as in the works of the 10 poets observed by Lilly? Did Tsvetaeva make rhymes in the
very special way or not? The connected problem I take into account is the perception of rhymes in
general, which I tested with two experiments. The first one considered the question about the
human ability to make rhymes and whether it differs between the common people and poets. The
second experiment considered the perception of the rhymes – whether the words with the high
ranked vowels are perceived as more pleasant to the reader than with the low ranked ones. I was
also aimed to find any correlation between rhymes and morphemes of the words and also with the
parts of speech; I also attempted to find similar effects in the clause-ending words in Tsvetaeva’s
prose.
For analysis I took 522 verse lines of the Tsvetaeva’s poems. All the verses were written
in the period 1906-1917 and have dactylic clausulae. To verify the hypothesis considering the
vowel distribution in prose I chose 597 clause-ending words from the two Tsvetaeva’s essays:
“About love” (“O lyubvi”) and “Vozrozhdenshchina”.
My analysis shows that the vowel distribution is the same as in Lilly 1987 (paroxytonic
words). The distribution within different morphemes and parts of speech does not provide a
plausible explanation of the bias. On the contrary, the observation of the clause-ending words in
the two Tsvetaeva’s essays shows almost the same stressed vowels distribution. That means that
the most plausible explanation of the biased distribution is in the effect of the clause-ending words.
The results of the experiments show us that people’s habits of making rhymes differ
significantly, though some of the obvious rhymes tend to cluster in the original poet’s word.
Experiments on perception of rhymes must be more sophisticated – in the conducted experiments
it was hard to divide phonetics from semantics of the poems.
References
Lilly 1987 – Ian K. Lilly. On stressed Russian rhyme and non-rhyme vowels // The Slavonic ans
East European review, V. 65, N. 3. – 1987.
Sozinova
Structure of Verse Workshop, Leiden University Centre for Linguistics
March 2015
Abstract
The Phenomenon of Bridge in Greek Stichic Verse
Dr Marlein van Raalte, Classics, Leiden University
In the study of ancient Greek verse the localization of word shapes remains a popular field of
research. In quantitative verse, just as syllables involving specific phonological combinations
are considered too heavy for particular verse positions, in some positions word-end is supposed
to be avoided because of the lengthening of word-final syllables.
Focusing on the latter subject, in this paper I shall argue that in most cases the phenomenon
of bridge in Greek stichic verse (dactylic hexameter, iambic trimeter, trochaic tetrameter
catalectic) can be explained in terms of rhythmical preferences (rising / falling movement,
pendant / blunt endings) in relation to the metrical groups involved — manifest in the caesura
positions and clausular phenomena. Even in the avoidance of split-resolution, i.e., word-end
between two short syllables filling a single metric element, the time factor does not seem to
play a role; the avoidance of split-resolution rather serves the identity of the verse element, the
perception of which is at risk when the syllables involved belong to two different words.
Porson’s Law (strict avoidance of word-end after a long syllable occupying the last anceps
position in the iambic trimeter and trochaic tetrameter) will serve as an example; it will be
argued that an explanation in rhythmical terms is likely also since it accounts for the fact that
this bridge is not observed in comedy.
Beekes, R.S.P. ‘On the Structure of the Greek Hexameter. O’Neill Interpreted.’ Glotta 50 (1972) 1–10
Bross, Christoph, Dieter Gunkel & Kevin M. Ryan ‘Caesurae, Bridges, and the Colometry of Four
Tocharian B Meters’, Indo-European Linguistics 2 (2104) 1–23
Devine, A.M. & L. D. Stevens, Language and Metre. Resolution, Porson's Bridge and Their Prosodic
Basis. Chico, CA 1984
---, The Prosody of Greek Speech. Oxford 1994
van Raalte, Marlein Rhythm and Metre. Towards a Systematic Description of Greek Stichic Verse.
Assen 1986
Sicking, C.M.J. Griechische Verslehre. München 1993
van Raalte
VerseTyp 2.0: A Database of Verse Forms in the Languages of the World S.Versace1, L. Magyar2-3, M. Dingemanse3
This paper outlines a new digital database for verse forms in the languages of the word, VerseTyp2. This database builds on the previous VerseTyp: a pilot digital database of rules of verse in the languages of the world (cf. Versace & Fabb 2012) and improves its architecture. To do that, VerseTyp2’s search mask adopts a new set of questions combining descriptive precision with enough generality to enhance usability for scholars of any field dealing with verse forms.
Differing from the original VerseTyp, we focus on the concept of ‘poetic(P-) feature’ (for example, rhyme) rather than on that of ‘rule’. We assume that designated features of language can become relevant to its representation in a verse form, in that such features are deployed according to non-linguistic, nonetheless systematic modes of organization, which are distinctive of the verse form (cf. Fabb 2010a). On what basis we can construct typological generalizations (e.g., why a specific language selects exactly P-feature X) or explanations motivated by other cognitive mechanisms (e.g. all verbal arts might have lineated verse), is, however, not yet clear.
VerseTyp2 tries to reformulate these questions without making assumptions about the rules that may account for these modes of organization. It provides instead a unified procedure for describing these modes of organization in the verse form. This stance is motivated by the present state of the typological inquiry on the variety of verse forms attested in the world’s languages, lacking data in some cases and a consistent mode of analysis and description in many others. To bridge this gap, VerseTyp2’s search mask defines a set of specific questions, designed so as to derive from two more general questions. We exemplify this by considering the Hungarian verse form exemplified below (cf. Weöres 1981), typically combining, among other features, two coexisting prominence patterns and fixed counting of syllables:
(1) a. Arany ágon ül a sármány, The ortolan sits on a golden branch, kicsi dalt fúj fuvoláján, plays a small song on her flute, arany égen ül a bárány, the lamb sits on golden sky, belezendít citeráján. plays on his zither.
b. ∪ ∪ _ ∪ ∪ ∪ _ _ ∪ = short/_ long a.rany á.gon / ül a sár.mány
X . x . X . x . X=++, x=+ stressed,/. = unstr.
VerseTyp2 takes the line to be the basic unit of analysis that defines whether a form is verse or not. The first general question we ask of the form is: What P-features does the verse have? All entries should answer the same sub-questions, relative to a) sectioning, and b) repetition. As for (a): does the form provide evidence for sections at the level of i) line (yes); ii) sub-line (yes); iii) super-line (yes). As for (b): iv) repetition of phonological structures, I – rhythm (yes: link to (i)); v) r. of phonological s., II – alliteration (no), rhyme (yes: rhyme ABAB; link to (i)); vi) r. of morphological s. – rhyme (yes, link to (i, ii)); vii) r. of syntactic s. – parallelism (yes, link to i, ii).
Subsequently, we ask a second general question: How does the verse implement its P-features? (i) Counting of syllables; (ii) 4th syllable is always followed by word boundary; (iii) sentence-intonational phrase boundary always follows the 4th line; (iv) markedness patterning (stressed-unstressed/short-short-long); (v) phonol. foot; (vi) as (v); (vii) by lexicon and syntax. To complete the encoding of the verse form, we envisage creating an online space for recordings and examples; and the latter will be required for each entry.
VerseTyp2 will thus lead to an online surface where verse forms of virtually any poetic tradition can be compared according to the set of questions we raise, cross-searched by feature and visualized on typological maps. To maximize interoperability and to guarantee long-term availability, we aim to host VerseTyp2 at CLLD (cross-linguistic linked databases), a service provided by the Max Planck Society which already hosts several of the better known cross-linguistic databases such as WALS and PHOIBLE.
This can lead to new insights about formal correlations among P-features and between verse forms and their source languages (cf. Fabb 2010b); these can, in turn, yield more robust typological generalizations on the spreading of verse forms in the world’s languages. VerseTyp2 will enable researchers to ‘speak one language’ when dealing with data about verse forms; and it will have a positive impact on formal theories of such forms (e.g. Hanson & Kiparsky 1996), thus furthering our formal understanding of poetry in the world’s languages.
Versace & Magyari & Dingemanse
REFERENCES Fabb, N. 2010a. Is literary language a development of ordinary language? Lingua, Vol 120, No. 5, pp. 1219-
1232 (2010). Fabb, N. 2010b. The Non-Linguistic in Poetic Language: a Generative Approach. Journal of Literary
Theory, 4.1:1-18. Fabb, N., G. Dunsire, S. Versace. 2010. VerseTyp: Rules for Verse in the World’s Languages. Digital
resource. URL: www.versetyp.cdlr.strath.ac.uk. University of Strathclyde. Versace, S. & N. Fabb. 2011. A database as a method of raising typological questions about poetic form.
Proceedings of the Conference on Language Documentation & Linguistic Theory 3, SOAS, UK, 289-296.
Weöres, S. 1981. Ha a világ rigó lenne [If the world would be a blackbird]. Móra Ference Könyvkiadó: Budapust.
1Max Planck Institute for Empirical Aesthetics Department of Language and Literature 2-3Pázmány Péter Catholic University Faculty of Humanities and Social Sciences Department of General Psychology 3Max Planck Institut for Psycholinguistics Department of Language and Cognition
Versace & Magyari & Dingemanse
