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Visualization of rhythm, time and metre

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Abstract

Developments in the theory of auditory processing of rhythmic signals have enabled the construction of a robust algorithm for recovery of rhythmic grouping structure. This algorithm appears to be effective for both speech and music signals. The theory upon which the algorithm was based was inspired by the theory of edge detection in vision. The output of the algorithm can be visualised in the form of a “rhythmogram”, examples of which are shown for a variety of speech signals. The relationship between rhythm, time perception and metre is discussed in the light of a recent “auditory-motor” theory of beat induction.

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References

  • Brown, G. J. (1992). Computational Auditory Scene Analysis: A Representational Approach. Ph.D. Thesis, University of Sheffield.

  • Brown, G. J. & Cooke, M. (1994). Perceptual Grouping of Musical Sounds: A Computational Model. J. New Music Research.

  • Clarke, E. (1988). Generative Principles in Musical Performance. In Sloboda, J. (ed.) Generative Processes in Music: The Psychology of Performance, Improvisation and Composition. Oxford: Claredon Press.

    Google Scholar 

  • Cutler, A. & Ladd, D. R. (1983). Prosody: Models and Measurement. Springer-Verlag: Berlin.

    Google Scholar 

  • Desain, P. (1992) A (De) Composable Theory of Rhythm Perception. Music Perception 9: 439–454.

    Google Scholar 

  • Dishal, M. (1959). Gaussian Response Filter Design. Electrical Communications 36(1): 3–26.

    Google Scholar 

  • Drake, C. & Botte, M. (1993). Tempo Sensitivity in Auditory Sequences: Evidence for a Multiple-Look Model. Perception and Psychophysics 54(3): 277–286.

    Google Scholar 

  • Geigerich, H. J. (1985). Metrical Phonology and Phonological Structure. Cambridge University Press: Cambridge.

    Google Scholar 

  • Glasberg, B. & Moore, B. (1990). Derivation of Auditory Filter Shapes from Notched-Noise Data. Hearing Research 47: 103–138.

    Google Scholar 

  • Hardy, T. (1923). Collected Poems of Thomas Hardy. Vol. I. London: Macmillan.

    Google Scholar 

  • Kingston, J. & Beckman, M. E. (1990). Papers in Laboratory Phonology: Between the Grammar and Physics of Speech. CUP: Cambridge.

    Google Scholar 

  • Large, E. (1994). The Resonant Dynamics of Beat Tracking and Meter Perception. Proceedings of The International Computer Music Conference. Denmark: Aarhaus.

    Google Scholar 

  • Lee, C. S. (1991). Perception of Metrical Structure: Experimental Evidence and a Model. In Howell, P., West, R. & Cross, I. (eds.) Representing Musical Structure, 59–127. London: Academic Press.

    Google Scholar 

  • Leman, M. (1994). Introduction to Auditory Models in Music Research. J. New Music Research 23(1): 5–9.

    Google Scholar 

  • Lerdahl, F. & Jackendoff, R. (1983). A Generative Theory of Tonal Music. MIT Press: Cambridge, MA.

    Google Scholar 

  • Liberman, M. & Prince, A. (1977). On Stress and Linguistic Rhythm. Linguistic Inquiry 8(2): 249–336.

    Google Scholar 

  • Longuet-Higgins, H. C. (1976). The Perception of Melodies. Nature 263: 646–653.

    Google Scholar 

  • Longuet-Higgins, H. C. & Lee, C. S. (1982). Perception of Musical Rhythms. Perception 11: 115–128.

    Google Scholar 

  • Longuet-Higgins, H. C. & Lee, C. S. (1984). The Rhythmic Interpretation of Monophonic Music. Music Perception 1(4): 424–441.

    Google Scholar 

  • Longuet-Higgins, H. C. & Steedman, M. J. (1971, 1987). On Interpreting Bach. In Longuet-Higgins, H. C. (ed.) Mental Processes: Studies in Cognitive Science, 82–104. MIT Press: Cambridge, MA.

    Google Scholar 

  • Marr, D. (1982). Vision. Freeman: New York.

    Google Scholar 

  • Meddis, R. (1988). Simulation of Auditory-Neural Transduction: Further Studies. J. Acoust. Soc. Am 83(3): 1056–1063.

    Google Scholar 

  • Parncutt, R. (1994). A Model of Beat Induction Accounting for Perceptual Ambiguity by Continuously Variable Parameters. Proceedings of The International Computer Music Conference. Denmark: Aarhaus.

    Google Scholar 

  • Patterson, R. D. & Holdsworth, J. (1992). A Functional Model of Neural Activity Patterns and Auditory Images. In Ainsworth, W. A. (ed.) Advances in Speech, Hearing and Language Processing. Vol. 3. JAI Press: London.

    Google Scholar 

  • Popper, A. N. & Fay, R. R. (1992). The Mammalian Anditory Pathway: Neurophysiology. Springer-Verlag: NY.

    Google Scholar 

  • Povel, D. J. & Essens, P. (1985). Perception of Temporal Patterns. Music Perception 2(4): 411–440.

    Google Scholar 

  • Repp, B. (1990). Patterns of Expressive Timing in Performances of a Beethoven Minuet by Nineteen Famous Painists. Journal of the Acoustical Society of America 88(2): 622–641.

    Google Scholar 

  • Repp, B. (1992). Probing the Cognitive Representation of Musical Time: Structural Constraints on the Perception of Timing Perturbatons. Cognition 44: 241–281.

    Google Scholar 

  • Rosenthal, D. (1992). Machine Rhythm: Computer Emulation of Human Rhythm Perception. MIT Media Lab. Ph.D Thesis.

  • Seashore, C. (1938). The Psychology of Music. McGraw-Hill: New York.

    Google Scholar 

  • Selkirk, E. (1984). Phonology and Syntax: The Relation between Sound and Structure. MIT Press: Cambridge, MA.

    Google Scholar 

  • Shaffer, H. (1981). Performances of Chopin, Bach and Bartok: Studies in Motor Programming. Cognitive Psychology 13: 326–376.

    Google Scholar 

  • Sloboda, J. (1983). The Communication of Musical Meter. Quarterly Journal Of Experimental Psychology 35: 377–396.

    Google Scholar 

  • Todd, N. P. (1985). A Model of Expressive Timing in Tonal Music. Music Perception 3: 33–58.

    Google Scholar 

  • Todd, N. P. McAngus (1989). Towards a Cognitive Theory of Expression: The Performance and Perception of Rubato. Contemporary Music Review 4: 405–416.

    Google Scholar 

  • Todd, N. P. McAngus (1992). The Dynamics of Dynamics: A Model of Musical Expression. J. Acoust. Soc. Am 91(6): 3540–3550.

    Google Scholar 

  • Todd, N. P. McAngus (1994a). The Auditory “primal sketch”: A Multi-Scale Model of Rhythm Grouping. J. New Music Research 23(1): 25–70.

    Google Scholar 

  • Todd, N. P. McAngus (1994b). A New Theory of Temporal Integration. British Journal of Audiology.

  • Todd, N. P. McAngus (1995). The Kinematics of Musical Expression. J. Acoust. Soc. Am 97(3), 1940–1950.

    Google Scholar 

  • Todd, N. P. McAngus & Brown, G. (1994). A Multi-Scale Auditory Model of Prosodic Perception. Proceedings of The International Conference on Spoken Language Processing. Yokoyama, Japan.

  • Todd, N. P. McAngus & Lee, C. S. (1994). An Auditory-Motor Model of Beat Induction. Proceedings of The International Computer Music Conference. Denmark: Aarhaus.

    Google Scholar 

  • Yost, W. A. & Sheft, S. (1993). Auditory Perception. In Yost, W., Popper, A. & Fay, R. (eds.) Human Psychophysics, 193–236. Springer-Verlag: NY.

    Google Scholar 

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McAngus Todd, N.P., Brown, G.J. Visualization of rhythm, time and metre. Artif Intell Rev 10, 253–273 (1996). https://doi.org/10.1007/BF00127682

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