Rethinking linguistic models of rhythm through evidence from jazz bop swing
Stephanie Shih, Stanford University
Jackendoff and Lerdahl's (1983; henceforth, GTTM) grid-based theory of
modeling musical intuitions of rhythm based on Western classical music
has formed a foundation for current research on both musical and
linguistic rhythm. Influenced by approaches in describing linguistic
rhythm, which have developed since the 1980s, this research at once
engages in the decades-old debates of metrical theory as well as
explores the limitations of linguistic theory for musical
description. When extended to non-classical forms, the GTTM grid
theory is too limited to accurately model and fully capture musical
intuitions governing the cognition of rhythm. From evidence in jazz
bop swing, a form whose rhythm is perceptibly distinct from that of
classical music, this paper develops revisions on the current
generative theory for describing musical rhythm.
Using data from Ella Fitzgerald recordings, I generate a metrical
model of jazz rhythm that departs from GTTM's model in three
significant ways. First, the polyphonic texture of jazz necessitates
the existence of two metrical models which together capture jazz's
rhythmic form, though these models are similar in many ways and may be
reconciled as one. Second, evidence from jazz supports an argument
that musical rhythm, like linguistic rhythm, involves the metrical
features of culminativity and constituency. This argument leads to
the use of a tree-based model for representing rhythm as opposed to
GTTM's grid-based model, which fails to demonstrate constituency
structure. Third, unlike the binary metrical model hitherto used to
describe musical rhythm, jazz rhythm requires ternary metrical
structure, like anapestic meters in poetics, accounting for both the
seemingly uneven rhythm of swing and jazz's conflict between stressing
phrasal beginnings and metrical prominent beats. This revised model,
based on jazz, accounts for more of the metrical relationships present
in music that possible in GTTM, permitting more flexibility and
comprehensiveness in describing listeners' intuitions of musical
rhythm. Furthermore, the model presented here more greatly reflects
models of linguistic rhythm, a significant conclusion in regards to
the similarities between language and music.
This talk will also be presented at the
International
Conference on Music Communication Science
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