Examination of Pronunciation Variation from Hand-Labelled Corpora

Abstract

Pronunciation variation examinations have two aims: to extent our phonetic, linguistic knowledge and to add variation models to automatic speech recognisers (ASR) to improve recognition accuracy. By examining pronunciation variation in Hungarian language on the corpus of the Hungarian Telephone Speech Database (MTBA), that contains semi-automatically labelled records from 500 speakers, we used a data driven approach. From the statistical analysis pronunciation matrices were constructed, both word-internal and cross-word pronunciation variation were examined separately and compared. Based on the results, pronunciation variation modeling is feasible for ASRs, or automatic phonetic transcription rules can be derived The examination was prepared based on the Hungarian speech databases, but the method is also adaptable for other languages.