Syllable detection in read and spontaneous speech

Automatic syllable detection is an important task when analysing very large speech corpora in order to answer questions concerning prosody, rhythm, speech rate, speech recognition and synthesis. In this paper a new method for automatic detection of syllable nuclei is presented. Two large spoken language corpora (PhonDatII, Verbmobil) were labelled by three phoneticians and then used to adjust the key parameters of the algorithm and to evaluate its error rate. Additionally, parts of the corpora were used to test the interand intraindividual consistency of the transcribers. The evaluation of the algorithm currently shows an error rate of 12.87% for read speech and 21.03% for spontaneous speech. The interindividual consistency of 95.8% might be considered as an upper limit for any automatic detection method.