Automatic phonetic transcription of large speech corpora

This study is aimed at investigating whether automatic phonetic transcription procedures can approximate manual transcriptions typically delivered with contemporary large speech corpora. To this end, ten automatic procedures were used to generate a broad phonetic transcription of well-prepared speech (read-aloud texts) and spontaneous speech (telephone dialogues) from the Spoken Dutch Corpus. The resulting transcriptions were compared to manually verified phonetic transcriptions from the same corpus. Most transcription procedures were based on lexical pronunciation variation modelling. The use of signal-based pronunciation variants prevented the approximation of the manually verified phonetic transcriptions. The use of knowledge-based pronunciation variants did not give optimal results either. A canonical transcription that, through the use of decision trees and a small sample of manually verified phonetic transcriptions, was modelled towards the target transcription, performed best. The number and the nature of the remaining disagreements with the reference transcriptions compared to inter-labeller disagreements reported in the literature.