Optimal models of prosodic prominence using the Bayesian information criterion

Tim Mahrt, Jui Ting Huang, Yoonsook Mo, Margaret Fleck, Mark Hasegawa-Johnson, Jennifer Cole

Research output: Contribution to journalConference article

Abstract

This study investigated the relation between various acoustic features and prominence. Past research has suggested that duration, pitch, and intensity all play a role in the perception of prominence. In our past work, we found a correlation between these acoustic features and speaker agreement over the placement of prominence. The current study was motivated by a need to enrich our understanding of this correlation. Using the Bayesian information criterion, we show that the best model for a feature that cues prosody is not necessarily a single Gaussian. Rather, the best model depends on the feature. This finding has consequences for our understanding of the role of these features in the perception of prosody and for prosody recognition systems.

Original languageEnglish (US)
Pages (from-to)2037-2040
Number of pages4
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
StatePublished - Dec 1 2011
Event12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy
Duration: Aug 27 2011Aug 31 2011

    Fingerprint

Keywords

  • Bayesian Information Criterion
  • Prominence
  • Prosody

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modeling and Simulation

Cite this