This paper reports on an experiment aimed at establishing how phonetic transcriptions for the large CGN corpus can be obtained most efficiently. This experiment explores the po tential of an automatically generated transcription (AGT) by comparing an AGT with a reference transcription (Tref) of the same material, to determine whether and how the AGT can be improved to make it more similar to Tref. The results indicate that the AGT can be optimized through pronunciation variation modelling so as to make human corrections more efficient or even superfluous, at least for some speech styles.
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