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.
Get full access to this article
View all access options for this article.
References
1.
AbrahamO.von HornbostelE. M. (1909–1910). Vorschläge für die Transkription exotischer Melodien. Sammelbände der Internationalen Musikgesellschaft, 1–25.
2.
AhlbaeckS. (1997). A computer-aided Method of analysis of melodic segmentation in monophonic Melodies. Proceedings of the 3rd Triennial ESCOM conference, 263–8.
3.
BaddeleyA. (1986). Working Memory. Oxford: Oxford University Press.
4.
BakerM. (1989). An artificial intelligence approach to musical grouping analysis. Contemporary Music Review, 3, 43–68.
5.
BalkwillL.ThompsonW. F. (1999) A Cross-Cultural Investigation of the Perception of Emotion in Music: Psychophysical Cues. Music Perception, 17 (1), 43–64.
6.
BlackingJ. (1973) How Musical is Man?Seattle: University of Washington Press.
7.
BregmanA. (1990). Auditory Scene Analysis. Cambridge, MA: MIT Press.
8.
BrownG. J. (1992a). Computational Auditory Scene Analysis. Unpublished PhD Thesis, Department of Computer Science, University of Sheffield. Technical Report CS-92-22.
9.
BrownG. (1992b). Musical fundamental frequency tracking using a pattern recognition method. Journal of the Acoustical Society of America, 92 (3), 1394–1402.
10.
BurnsE. M. (1999). Intervals, Scales and Tuning. In DeutschD. (ed.), The Psychology of Music (pp. 215–64). San Diego: Academic Press.
11.
CambouropoulosE. (1996). A Formal Theory for the Discovery of Local Boundaries in a Melodic Surface. Proceedings of the III Journées d'Informatique Musicale, Caen, France, 67–70.
12.
CookN. (1994). Perception: A perspective from music theory. In AielloR. and SlobodaJ. (eds), Musical Perceptions (pp. 64–95). New York: Oxford University Press.
13.
Crossley-HollandP. (ed.) (1974). Selected Reports in Ethnomusicology, 2 (1).
14.
DarwinC. J.CarlyonR. P. (1995). Auditory Grouping. In MooreB.C.J. (ed.), Handbook of Perception and Cognition, Volume 6, Hearing (pp. 387–424). Orlando, Florida: Academic Press.
15.
DensmoreF. (1909). Chippewa Music. Washington: Government Printing Office.
16.
DeliègeI. (1987). Grouping conditions in Listening to Music: An Approach to Lerdahl and Jackendoff's Grouping Preference Rules. Music Perception, 4 (4), 325–60.
17.
ErdelyS.ChipmanR. (1972). Strip-chart recording of narrow band frequency analysis in aid of ethno musicological data. 1972 Yearbook of the International Folk Music Council, 120–36.
18.
FletcherH.MunsonW. A. (1933). Loudness, its definition, measurement and calculation. Journal of the Acoustical Society of America, 5, 82–108.
19.
FraserA.FujinagaI. (1999). Toward realtime recognition of acoustic musical instruments. Proceedings of the International Computer Music Conference 99, Beijing, China, 175–7.
20.
FribergA.BresinR.FrydenL.SundbergJ. (1998). Musical Punctuation on the Microlevel: Automatic Identification and Performance of Small Melodic Units. Journal of New Musical Research, 27 (3), 271–92.
21.
FribergA.SundbergJ. (1999). Does music performance allude to locomotion? A model of final ritardandi derived from measurements of stopping runners. Journal of the Acoustical Society of America, 10 (3), 1469–84.
22.
FujieL. (1992). East Asia/Japan. In TitonTodd J. (ed.), Worlds of Music: an introduction to the music of the world's peoples (pp. 318–75). New YorkSchirmer Books.
23.
GreyJ. M. (1977). Multidimensional perceptual scaling of musical timbres. Journal of the Acoustical Society of America, 61 (5), 1270–7.
24.
GrossbergS. (2000). The complementary brain: Unifying brain dynamics and modularity. Trends in Cognitive Sciences, 4, 233–46.
25.
HajdaJ. M.KendallR. A.CarteretteE. C.HarshbergerM. L. (1997). Methodological issues in timbre research. In DeliègeI. and SlobodaJ. (eds), Perception and Cognition of Music (pp. 253–305). Taylor & Francis: Psychology Press.
26.
HahnJ.MuenzelS. (1995). Knochenfloeten aus dem Aurignacien des Geissenkloesterle bei Blaubeuren, Alb-Donau-Kreis. Fundberichte aus Baden-Wuerttemberg, 20, 1–12.
27.
HandelS. (1995). Timbre perception and auditory object identification. In MooreB. C. J. (ed.), Hearing (pp. 425–61). New York: Academic Press.
28.
HenebryR. (1928). A handbook of Irish music. London: Cork University Press.
29.
von HippelP. T. (ed.) (1998). 42 Ojibwa songs in the Humdrum kern representation: Electronic transcriptions from the Densmore collections [computer database] .
30.
HoutsmaA. J. M. (1997). Pitch and Timbre: Definition, Meaning and Use. Journal of New Music Research, 26, 104–15.
31.
HowardD. M.AngusJ. (1996). Acoustics and Psychoacoustics. Oxford: Focal Press.
32.
IversonP.KrumhanslC. L. (1993). Isolating the dynamic attributes of musical timbre. Journal of the Acoustical Society of America, 94 (5), 2595–2603.
33.
JensenK. (1999). Timbre Models of Musical sounds. Unpublished PhD Thesis. University of Copenhagen.
34.
JonesM. R. (1987). Dynamic pattern structure in music: recent theory and research. Perception and Psychophysics, 41 (6), 621–34.
35.
JonesM. R.BoltzM. (1989). Dynamic Attending and Responses to Time. Psychological Review, 96 (3), 459–91.
36.
KeilC.FeldS. (1995). Music Grooves: Essays and Dialogues. Chicago: University of Chicago Press.
37.
KeilC.KeilA. (1966). Musical Meaning A preliminary Report. Ethnomusicology, 10 (2) 153–73.
38.
LemanM. (1997). The Convergence Paradigm, Ecological Modelling, and Context-Dependent Pitch Perception. Journal of New Music Research, 26, 133–53.
39.
LerdahlF.JackendoffR. (1983). A Generative Theory of Tonal Music. Cambridge, MA: MIT Press.
40.
MartinK. D. (1999). Sound-Source Recognition: A theory and Computational Model Unpublished PhD Thesis. Massachusetts Institute of Technology.
41.
McAdamsS. (1989). Psychological Constraints on Form Bearing Dimensions in Music. Contemporary Music Review, 4 (1), 181–98.
42.
McAdamsS. (1999). Perspectives on the Contribution of Timbre to Musical Structure. Computer Music Journal, 23 (3), 85–102.
43.
MulheirG. (1991). The structure and function of the “sean-nós” tradition in Connemara, Ireland and the effects of outside influence on the Irish oral tradition, vol. I & II. Unpublished manuscript with the University of Sheffield.
44.
NarmourE. (1990). The Analysis and Cognition of Basic Melodic Structures. Chicago: University of Chicago Press.
45.
ParsonsT. W. (1976). Separation of speech from interfering speech by means of harmonic selection. Journal of the Acoustical Society of America, 60 (4), 911–8.
46.
RossingT. D. (1990). The Science of Sound Addison-Wesley.
47.
SachsC. (1962). The Wellsprings of Music. The Hague: Martinus Nijhoff.
48.
SchellenbergE. G. (1997). Simplifying the Implication Realization Model of Melodic Expectancy. Music Perception, 14 (3), 295–318.
49.
ScheirerE. D. (2000). Music-Listening Systems. Unpublished PhD Thesis. Massachusetts Institute of Technology.
50.
SeegerC. (1958). Prescriptive and Descriptive Music-Writing. The Musical Quarterly, 44 (2), 184–95.
51.
SegallM. H.CampbellD. T.HerskovitsM. J. (1966). Influence of culture on visual perception. Indianapolis, IN: Bobbs-Merrill.
52.
Selfridge-FieldE. (ed.). (1997). Beyond MIDI — The Handbook of Musical Codes. Cambridge, MA: MIT Press.
53.
SerafineM. L. (1988). Music as Cognition. New York: Columbia University Press.
54.
ŠermanM.GriffithN.Scar;ermanN. (2000). Computational modelling of segmentation processes in unaccompanied melodies. International Conference on Music Perception and Cognition, Keele, UK, July 2000, 963–73.
55.
SetharesW. A. (1998). Tuning timbre, spectrum, scale. London: Springer-Verlag.
56.
ShafferL. H.ClarkeE. E.ToddN. P. (1985). Metre and rhythm in piano playing. Cognition, 20, 61–77.
57.
StammenD. R.PennycookB. (1994). Real-time segmentation of music using an adaptation of Lerdahl and Jackendoff's Grouping Principles. Proceedings of the 3rd International Conference on Music Perception and Cognition, Liège, Belgium: European Society for the Cognitive Sciences of Music, 268–70.
58.
ToddN. P. McAngusClarkeE. F. (1995). The perception of rhythmic structure in expressive musical performance. Proceedings of the 15th International Congress on Acoustics, Vol III, 459–62.
59.
ToddN. P. McAngusO'BoyleD. J.LeeC. S. (1999). A Sensory-Motor Theory of Rhythm, Time Perception and Beat Induction. Journal of New Music Research, 28 (1), 5–28.
60.
WishartT. (1996). On sonic art, EmersonS. (ed.). Amsterdam: Harwood Academic Publishers.
61.
WitkinH. A.LewisH. B.HertzmanM.MachoverK.MeissnerP. B.WarpnerS. (1954). Personality through perception. New York: Harper.
