Long-distance rhythmic dependencies and their application to automatic language identification

摘要

The perception of rhythmic differences among languages relies on varieties in periodicity within prominence groups. But the consensus in phonetic research on rhythm is that existing measures don't capture true rhythm by that definition - instead, they merely measure short-term timing. This work proposes a new rhythm measure, the Generalized Variability Index (GVI), that examines durational contexts over arbitrarily long linguistic distances. To evaluate this new measure, we conducted a set of experiments in automatic language identification using large amounts of data from 11 languages in the Globalphone and TIMIT corpora. When added to baseline rhythm measures, these new GVI features offer absolute improvement in 11-way language classification accuracy by as much as 12%. Moreover, the addition of wider and wider durational context in the GVI continues to contribute information useful for automatic language ID, abating in usefulness only at a distance of about 10 syllables.