On the sufficiency of automatic phonetic transcriptions for pronunciation variation research

W e investigated whether automatic phonetic transcriptions (APTs) can replace manually verified phonetic transcriptions (MPTs) in a large corpus-based study on pronunciation variation. To this end, we compared the performance o f both transcription types in a classification experiment aimed at establishing the direct influence o f a particular situational setting on pronunciation variation. W e trained classifiers on the speech processes extracted from the alignments o f an APT and an MPT with a canonical transcription. W e tested whether the classifiers were equally good at verifying whether unknown transcriptions represent read speech or telephone dialogues, and whether the same speech processes were identified to distinguish between transcriptions o f the two situational settings. Our results not only show that similar distinguishing speech processes were identified; our APT-based classifier yielded better classification accuracy than the MPT-based classifier whilst using fewer classification features.