Title :
Automatic detection of “g-dropping” in American English using forced alignment
Author :
Yuan, Jiahong ; Liberman, Mark
Author_Institution :
Univ. of Pennsylvania, Philadelphia, PA, USA
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”.
Keywords :
natural language processing; speech processing; American English; KL-divergence; Penn phonetics lab forced aligner; acoustic model; automatic detection; forced alignment; g-dropping; nasal codas; native Mandarin speaker; probable pronunciation; vowel quality; Acoustics; Computational modeling; Educational institutions; Hidden Markov models; Humans; Pragmatics; Speech;
Conference_Titel :
Automatic Speech Recognition and Understanding (ASRU), 2011 IEEE Workshop on
Conference_Location :
Waikoloa, HI
Print_ISBN :
978-1-4673-0365-1
Electronic_ISBN :
978-1-4673-0366-8
DOI :
10.1109/ASRU.2011.6163980