8th European Conference on Speech Communication and Technology

Geneva, Switzerland
September 1-4, 2003


Automatic Prosodic Prominence Detection in Speech Using Acoustic Features: An Unsupervised System

Fabio Tamburini

University of Bologna, Italy

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 nuclei duration and mid-to-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. This system does not require any training phase, additional information or annotation, it is not tailored to a specific set of data and can be easily adapted to different languages.

Full Paper

Bibliographic reference.  Tamburini, Fabio (2003): "Automatic prosodic prominence detection in speech using acoustic features: an unsupervised system", In EUROSPEECH-2003, 129-132.