Sonority as a Basis for Rhythmic Class Discrimination. Antonio Galves, USP. Jesus Garcia, USP. Denise Duarte, USP and UFGo. Charlotte Galves, UNICAMP. The starting point : Ramus, Nespor & Mehler (1999). What we do.
Sonority as a Basis for Rhythmic Class Discrimination
Antonio Galves, USP.
Jesus Garcia, USP.
Denise Duarte, USP and UFGo.
Charlotte Galves, UNICAMP.
Applied to the same linguistic samples considered in RNM, our approach produces the same clusters corresponding to the three conjectured rhythmic classes.
Duarte et al. (2001) propose a parametric family of probability distributions that closely fit the data in RNM.
This has two advantages:
Goal: to define a function that maps local windows of the signal on the interval [0,1]. This function should assign
pt(f) = re-normalized power spectrum for frequency f around time t.
This re-normalization makes pt a probability measure.
A regular pattern characteristic of sonorant spans will produce a sequence of probability measures which are close in the sense of relative entropy.
This suggests defining the function sonority as