Sonority as a basis for rhythmic class discrimination

Abstract

Recently, several papers, starting with Ramus, Nespor and Mehler (1999), gave evidence that simple statistics of the speech signal could discriminate between different rhythmic classes.In the present paper, we propose a new approach to the problem of finding acoustic correlates of the rhythmic classes.Its main ingredient is a rough measure of sonority defined directly from the spectrogram of the signal.This approach has the major advantage that it can be implemented in an entirely automatic way, with no need of previous hand-labelling of the acoustic signal.Applied to the same linguistic samples considered in RNM, it produces the same clusters corresponding to the three conjectured rhythmic classes.

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