Low-resource Accent Classification in Geographically-proximate Settings: A Forensic and Sociophonetics Perspective. (arXiv:2206.12759v2 [cs.CL] UPDATED)

Accented speech recognition and accent classification are relatively
under-explored research areas in speech technology. Recently, deep
learning-based methods and Transformer-based pretrained models have achieved
superb performances in both areas. However, most accent classification tasks
focused on classifying different kinds of English accents and little attention
was paid to geographically-proximate accent classification, especially under a
low-resource setting where forensic speech science tasks usually encounter. In
this paper, we explored three main accent modelling methods combined with two
different classifiers based on …

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