AMuSE Grouping

An implementation of several cognitive models of melodic grouping perception.

Includes implementations and unified interface to:

• the Grouping Preference Rules (GPRs) of the General Theory of Tonal Music (Lerdahl and Jackendoff, 1983; Frankland & Cohen, 2004);
• Local Boundary Detection Model, LBDM (Cambouropoulos, 2001);
• statistical segmentation (Saffran et al., 1999; Brent, 1999).

See the Wiki for usage.

References¶

Brent, M. R. (1999a). An efficient, probabilistically sound algorithm
for segmentation and word discovery. Machine Learning, 34(1-3),
71-105.

Cambouropoulos, E. (1998). Towards a General Computational Theory of
Musical Structure. Doctoral dissertation, The University of Edinburgh,
Faculty of Music and Department of Artificial Intelligence.

Cambouropoulos, E. (2001). The local boundary detection model (LBDM)
and its application in the study of expressive timing. In Proceedings
of the International Computer Music Conference (pp. 232-235). Havana,
Cuba.

Frankland, B. W. and Cohen, A. J. (2004). Parsing of melody:
Quantification and testing of the local grouping rules of Lerdahl and
Jackendoff's A Generative Theory of Tonal Music. Music Perception,
21(4), 499­-543.

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

Saffran, J. R., Johnson, E. K., Aslin, R. N., & Newport, E. L. (1999).
Statistical learning of tone sequences by human infants and adults.
Cognition, 70(1), 27-52.