Automatic detection of “g-dropping” in American English using forced alignment

Abstract

This study investigated the use of forced alignment for automatic detection of “g-dropping” in American English (e.g., walkin'). Two acoustic models were trained, one for -in' and the other for -ing. The models were added to the Penn Phonetics Lab Forced Aligner, and forced alignment will choose the more probable pronunciation from the two alternatives. The agreement rates between the forced alignment method and native English speakers ranged from 79% to 90%, which were comparable to the agreement rates among the native speakers (79% – 96%). The two variations of pronunciation not only differed in their nasal codas, but also - and even more so - in their vowel quality. This is shown by both the KL-divergence between the two models, and that native Mandarin speakers performed poorly on classification of “g-dropping”.