How Rhythmical is Hexameter: A Statistical Approach to Ancient Epic Poetry

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  1. 1. Maciej Eder

    Polish Academy of Sciences

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In this paper, I argue that the later a given specimen of hexamater
is, the less rhythmical it tends to be. A brief discussion of
the background of ancient Greek and Latin metrics and its
connections to orality is followed by an account of spectral
density analysis as my chosen method. I then go on to comment
on the experimental data obtained by representing several
samples of ancient poetry as coded sequences of binary values.
In the last section, I suggest how spectral density analysis may
help to account for other features of ancient meter.
The ancient epic poems, especially the most archaic Greek
poetry attributed to Homer, are usually referred as an
extraordinary fact in the history of European literature. For
present-day readers educated in a culture of writing, it seems
unbelievable that such a large body of poetry should have
been composed in a culture based on oral transmission. In
fact, despite of genuine singers’ and audience’s memory, epic
poems did not emerge at once as fi xed texts, but they were
re-composed in each performance (Lord 2000, Foley 1993,
Nagy 1996). The surviving ancient epic poetry displays some
features that refl ect archaic techniques of oral composition,
formulaic structure being probably the most characteristic
(Parry 1971: 37-117).
Since formulaic diction prefers some fi xed rhythmical patterns
(Parry 1971: 8-21), we can ask some questions about the role
of both versifi cation and rhythm in oral composition. Why was
all of ancient epic poetry, both Greek and Latin, composed
in one particular type of meter called hexameter? Does the
choice of meter infl uence the rhythmicity of a text? Why does
hexameter, in spite of its relatively restricted possibilities of
shaping rhythm, differ so much from one writer to another
some (cf. Duckworth 1969: 37-87)? And, last but not least,
what possible reasons are there for those wide differences
between particular authors?
It is commonly known that poetry is in general easier to
memorize than prose, because rhythm itself tends to facilitate
memorization. In a culture without writing, memorization is
crucial, and much depends on the quality of oral transmission.
In epic poems from an oral culture rhythm is thus likely to
be particularly important for both singers and hearers, even
though they need not consciously perceive poetic texts as
rhythmical to benefi t from rhythm as an aid to memory. It may then be expected on theoretical grounds that non-oral
poems, such as the Latin epic poetry or the Greek hexameter
of the Alexandrian age, will be largely non-rhythmical, or at
least display weaker rhythm effects than the archaic poems
of Homer and Hesiod. Although formulaic diction and other
techniques of oral composition are noticeable mostly in
Homer’s epics (Parry 1971, Lord 2000, Foley 1993, etc.), the
later hexameters, both Greek and Latin, also display some
features of oral diction (Parry 1971: 24-36). The metrical
structure of hexameter might be quite similar: strongly
rhythmical in the oldest (or rather, the most archaic) epic
poems, and less conspicuous in poems composed in written
form a few centuries after Homer. The aim of the present
study is to test the hypothesis that the later a given specimen
of hexameter is, the less rhythmical it tends to be.
Because of its nature versifi cation easily lends itself to statistical
analysis. A great deal of work has already been done in this
fi eld, including studies of Greek and Latin hexameter (Jones
& Gray 1972, Duckworth 1969, Foley 1993, etc.). However,
the main disadvantage of the methods applied in existing
research is that they describe a given meter as if it were a set
of independent elements, which is actually not true. In each
versifi cation system, the specifi c sequence of elements plays
a far more important role in establishing a particular type of
rhythm than the relations between those elements regardless
their linear order (language “in the mass” vs. language “in the
line”; cf. Pawlowski 1999).
Fortunately, there are a few methods of statistical analysis
(both numeric and probabilistic) that study verse by means
of an ordered sequence of elements. These methods include,
for example, time series modeling, Fourier analysis, the theory
of Markov chains and Shannon’s theory of information. In the
present study, spectral density analysis was used (Gottman
1999, Priestley 1981, etc.). Spectral analysis seems to be a very
suitable tool because it provides a cross-section of a given
time series: it allows us to detect waves, regularities and cycles
which are not otherwise manifest and open to inspection. In
the case of a coded poetry sample, the spectrogram shows
not only simple repetitions of metrical patterns, but also
some subtle rhythmical relations, if any, between distant lines
or stanzas. On a given spectrogram, a distinguishable peak
indicates the existence of a rhythmical wave; numerous peaks
suggest a quite complicated rhythm, while a pure noise (no
peaks) on the spectrogram refl ects a non-rhythmical data.
To verify the hypothesis of hexameter’s decreasing rhythmicity,
7 samples of Greek and 3 samples of Latin epic poetry were
chosen. The specifi c selection of sample material was as
follows: 3 samples from Homeric hexameter (books 18 and
22 from the Iliad, book 3 from the Odyssey), 1 sample from
Hesiod (Theogony), Apollonius (Argonautica, book 1), Aratos
(Phainomena), Nonnos (Dionysiaca, book 1), Vergil (Aeneid,
book 3), Horace (Ars poetica), and Ovid (Metamorphoses,
book 1). In each sample, the fi rst 500 lines were coded in
such a way that each long syllable was assigned value 1, and
each short syllable value 0. Though it is disputed whether
ancient verse was purely quantitative or whether it also
had some prosodic features (Pawlowski & Eder 2001), the
quantity-based nature of Greek and Roman meter was never
questioned. It is probable that rhythm was generated not only
by quantity (especially in live performances), but it is certain
that quantity itself played an essential role in ancient meter.
Thus, in the coding procedure, all prosodic features were left
out except the quantity of syllables (cf. Jones & Gray 1972,
Duckworth 1969, Foley 1993, etc.). A binary-coded series was
then obtained for each sample, e.g., book 22 of the Iliad begins
as a series of values:
1110010010010011100100100100111001110010010011...
The coded samples were analyzed by means of the spectral
density function. As might be expected, on each spectrogram
there appeared a few peaks indicating the existence of several
rhythmical waves in the data. However, while the peaks
suggesting the existence of 2- and 3-syllable patterns it the text
were very similar for all the spectrograms and quite obvious,
the other peaks showed some large differences between the
samples. Perhaps the most surprising was the peak echoing
the wave with a 16-syllable period, which could be found in the
samples of early Greek poems by Homer, Hesiod, Apollonius,
and Aratos (cf. Fig. 1). The same peak was far less noticeable in
the late Greek hexameter of Nonnos, and almost absent in the
samples of Latin writers (cf. Fig. 2). Other differences between
the spectrograms have corroborated the observation: the
rhythmical effects of the late poems were, in general, weaker
as compared with the rich rhythmical structure of the earliest,
orally composed epic poems.
Although the main hypothesis has been verifi ed, the results also
showed some peculiarities. For example, the archaic poems by
Homer and Hesiod did not differ signifi cantly from the poems
of the Alexandrian age (Apollonius, Aratos), which was rather
unexpected. Again, the rhythm of the Latin hexameter turned
out to have a different underlying structure than that of all the
Greek samples. There are some possible explanations of those
facts, such as that the weaker rhythm of the Latin samples
may relate to inherent differences between Latin and Greek.
More research, both in statistics and in philology, is needed,
however, to make such explanations more nuanced and more
persuasive. Bibliography
Duckworth, George E. Vergil and Classical Hexameter Poetry:
A Study in Metrical Variety. Ann Arbor: University of Michigan
Press, 1969.
Foley, John Miles. Traditional Oral Epic: “The Odyssey”, “Beowulf ”
and the Serbo-Croatian Return Song. Berkeley: University of
California Press, 1993.
Gottman, John Mordechai, and Anup Kumar Roy. Sequential
Analysis: A Guide for Behavioral Researchers. Cambridge:
Cambridge University Press, 1990.
Jones, Frank Pierce, and Florence E. Gray. Hexameter
Patterns, Statistical Inference, and the Homeric Question: An
Analysis of the La Roche Data.Transactions and Proceedings of
the American Philological Association 103 (1972): 187-209.
Lord, Albert B. Ed. Stephen Mitchell and Gregory Nagy. The
Singer of Tales. Cambridge, MA: Harvard University Press,
2000.
Nagy, Gregory. Poetry as Performance: Homer and Beyond.
Cambridge: Cambridge University Press, 1996.
Parry, Milman. Ed. Adam Parry. The Making of Homeric Verse:
The Collected Papers of Milman Parry. Oxford: Clarendon Press,
1971.
Pawlowski, Adam. Language in the Line vs. Language in the
Mass: On the Effi ciency of Sequential Modeling in the Analysis
of Rhythm. Journal of Quantitative Linguistics 6.1 (1999): 70-77.
Pawlowski, Adam, and Maciej Eder. Quantity or Stress?
Sequential Analysis of Latin Prosody. Journal of Quantitative
Linguistics 8.1 (2001): 81-97.
Priestley, M. B. Spectral Analysis and Time Series. London:
Academic Press, 1981.

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Complete

ADHO - 2008

Hosted at University of Oulu

Oulu, Finland

June 25, 2008 - June 29, 2008

135 works by 231 authors indexed

Conference website: http://www.ekl.oulu.fi/dh2008/

Series: ADHO (3)

Organizers: ADHO

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