Review of A generative theory of tonal music.

1983 ◽  
Vol 3 (1) ◽  
pp. 60-67 ◽  
Author(s):  
Henry L. Cady
2004 ◽  
Vol 21 (4) ◽  
pp. 499-543 ◽  
Author(s):  
Bradley W. Frankland ◽  
Annabel J. Cohen

In two experiments, the empirical parsing of melodies was compared with predictions derived from four grouping preference rules of A Generative Theory of Tonal Music (F. Lerdahl & R. Jackendoff, 1983). In Experiment 1 (n = 123), listeners representing a wide range of musical training heard two familiar nursery-rhyme melodies and one unfamiliar tonal melody, each presented three times. During each repetition, listeners indicated the location of boundaries between units by pressing a key. Experiment 2 (n = 33) repeated Experiment 1 with different stimuli: one familiar and one unfamiliar nursery-rhyme melody, and one unfamiliar, tonal melody from the classical repertoire. In all melodies of both experiments, there was good within-subject consistency of boundary placement across the three repetitions (mean r = .54). Consistencies between Repetitions 2 and 3 were even higher (mean r = .63). Hence, Repetitions 2 and 3 were collapsed. After collapsing, there was high between-subjects similarity in boundary placement for each melody (mean r = .62), implying that all participants parsed the melodies in essentially the same (though not identical) manner. A role for musical training in parsing appeared only for the unfamiliar, classical melody of Experiment 2. The empirical parsing profiles were compared with the quantified predictions of Grouping Preference Rules 2a (the Rest aspect of Slur/Rest), 2b (Attack-point), 3a (Register change), and 3d (Length change). Based on correlational analyses, only Attack-point (mean r = .80) and Rest (mean r = .54) were necessary to explain the parsings of participants. Little role was seen for Register change (mean r = .14) or Length change (mean r = ––.09). Solutions based on multiple regression further reduced the role for Register and Length change. Generally, results provided some support for aspects of A Generative Theory of Tonal Music, while implying that some alterations might be useful.


1985 ◽  
Vol 4 (3) ◽  
pp. 292
Author(s):  
David Harvey ◽  
Fred Lerdahl ◽  
Ray Jackendoff

Author(s):  
Fred Lerdahl ◽  
Ray S. Jackendoff

1984 ◽  
Vol 8 (4) ◽  
pp. 56 ◽  
Author(s):  
Peter Child ◽  
Fred Lerdahl ◽  
Ray Jackendoff

2002 ◽  
Vol 6 (2) ◽  
pp. 149-184 ◽  
Author(s):  
A Ŝerman ◽  
Niall J. L. Griffith

This paper describes preliminary research towards the development of a system that can be used to investigate the mechanisms and representations underlying segmentation and phrase structure in music. It discusses the use of rules and principles in The Generative Theory of Tonal Music (Lerdahl and Jackendoff, 1983) and Implication Realization Model (Narmour, 1990). It also discusses the limitations of score notation as the basis for analysis and modelling of melodic segmentation, with reference to the problems associated withtranscribing non-Western music that uses different scales and exploits different organisations of melodic descriptors. This discussion provides a rationale for a methodology thatcan be applied to recorded music rather than notation. It describes MusicTracker — a toolthat extracts measures of change in pitch, dynamics and timbre fromrecordings of monophonic melodies. The use of this tool is illustrated with short fragments of musicfrom Japan, Burundi and Gabon.


1985 ◽  
Vol 29 (1) ◽  
pp. 145 ◽  
Author(s):  
Fred Lerdahl ◽  
Ray Jackendoff ◽  
Wayne Slawson

2014 ◽  
Vol 20 (3) ◽  
Author(s):  
Jordan B. L. Smith ◽  
Isaac Schankler ◽  
Elaine Chew

Some important theories of music cognition, such as Lerdahl and Jackendoff’s (1983)A Generative Theory of Tonal Music, posit an archetypal listener with an ideal interpretation of musical structure, and many studies of the perception of structure focus on what different listeners have in common. However, previous experiments have revealed that listeners perceive musical structure differently, depending upon their music background and their familiarity with the piece. It is not known what other factors contribute to differences among listeners’ formal analyses, but understanding these factors may be essential to advancing our understanding of music perception.We present a case study of two listeners, with the goal of identifying the differences between their analyses, and explaining why these differences arose. These two listeners analyzed the structure of three performances, a set of improvised duets. The duets were performed by one of the listeners and Mimi (Multimodal Interaction for Musical Improvisation), a software system for human-machine improvisation. The ambiguous structure of the human-machine improvisations as well as the distinct perspectives of the listeners ensured a rich set of differences for the basis of our study.We compare the structural analyses and argue that most of the disagreements between them are attributable to the fact that the listeners paid attention to different musical features. Following the chain of causation backwards, we identify three more ultimate sources of disagreement: differences in the commitments made at the outset of a piece regarding what constitutes a fundamental structural unit, differences in the information each listener had about the performances, and differences in the analytical expectations of the listeners.


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