Automatic detection of prosodic prominence in continuous 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 (F0) movements and syllable overall energy, and stress, which exhibits a strong correlation with syllable duration and high-frequency emphasis. By deriving a set of acoustic parameters it is possible to build syllable-stress detectors as well as pitch-accent detectors and combine them to build an automatic system devoted to prominence detection. Starting from a syllable-segmented utterance, the system presented here is capable of correctly identify prominent syllables with an agreement, with human-tagged data, comparable with the inter-human agreement reported in the literature.