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

  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. Hexameter’s decreasing rhythmicity is then illustrated
with reference to particular authors. 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 fixed texts, but they were
re-composed in each performance (Lord 2000, Foley 1993,
Nagy 1996). The surviving ancient epic poetry displays some
features that reflect archaic techniques of oral composition,
formulaic structure being probably the most characteristic (Parry
1971: 37-117).
Since formulaic diction prefers some fixed rhythmical patterns
(Parry 1971: 8-21), we can ask some questions about the role
of both versification 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 influence 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 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 benefit 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 versification easily lends itself to statistical
analysis. A great deal of work has already been done in this
field, 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
versification system, the specific 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.
To verify the hypothesis of hexameter’s decreasing rhythmicity,
7 samples of Greek and 3 samples of Latin epic poetry were
chosen. The specific 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 first 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 possible
that rhythm was generated not only by quantity, 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:
The coded samples were analyzed by means of the spectral
density function. As might be expected, on each spectogram
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 spectograms 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. The same peak was far less noticeable in the late
Greek hexameter of Nonnos, and totally absent in the samples
of Latin writers. Other differences between the spectograms
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
Although the main hypothesis has been verified, the results
also showed some peculiarities. For example, the archaic poems
by Homer and Hesiod did not differ significantly 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,
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 Efficiency of Sequential Modeling in the Analysis
of Rhythm." Journal of Quantitative Linguistics 6.1 (1999):
Pawlowski, Adam, and Maciej Eder. "Quantity or Stress?
Sequential Analysis of Latin Prosody." Journal of Quantitative
Linguistics 8.1 (2001): 81-97.
Priestly, M. B. Spectral Analysis and Time Series. London:
Academic Press, 1981.

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Conference Info


ADHO - 2007

Hosted at University of Illinois, Urbana-Champaign

Urbana-Champaign, Illinois, United States

June 2, 2007 - June 8, 2007

106 works by 213 authors indexed

Series: ADHO (2)

Organizers: ADHO

  • Keywords: None
  • Language: English
  • Topics: None