Prosodic prominence detection in speech

This paper presents work in progress on the automatic detection of prosodic prominence in continuous speech. Prosodic prominence involves two different phonetic features: pitch accents, connected with fundamental frequency (FO) movements and syllable overall energy, and stress, which exhibits a strong correlation with syllable nuclei duration and high-frequency emphasis. By measuring these acoustic parameters it is possible to build an automatic system capable of correctly identifying prominent syllables with an agreement with human-tagged data comparable with the inter-human agreement reported in the literature. These results were achieved without using any information apart from acoustic parameters.