Prosody for the eyes: Quantifying visual prosody using guided principal component analysis

Erin Cvejic, Jeesun Kim, Chris Wayne Davis, Guillaume Gibert

Research output: Contribution to conferencePaper

13 Citations (Scopus)

Abstract

Although typically studied as an auditory phenomenon, prosody can also be conveyed by the visual speech signal, through increased movements of articulators during speech production, or through eyebrow and rigid head movements. This paper aimed to quantify such visual correlates of prosody. Specifically, the study was concerned with measuring the visual correlates of prosodic focus and prosodic phrasing. In the experiment, four participants' speech and face movements were recorded while they completed a dialog exchange task with an interlocutor. Acoustic analysis showed that prosodic contrasts differed on duration, pitch and intensity parameters, which is consistent with previous findings in the literature. The visual data was processed using guided principal component analysis. The results showed that compared to the broad focused statement condition, speakers produced greater movement on both articulatory and non-articulatory parameters for prosodically focused and intonated words.

Original languageEnglish
Pages1433-1436
Number of pages4
Publication statusPublished - 1 Dec 2010
Event11th Annual Conference of the International Speech Communication Association: Spoken Language Processing for All, INTERSPEECH 2010 -
Duration: 26 Sep 2010 → …

Conference

Conference11th Annual Conference of the International Speech Communication Association: Spoken Language Processing for All, INTERSPEECH 2010
Period26/09/10 → …

Keywords

  • Guided principal components analysis
  • Inter-speaker variation
  • Prosody
  • Speech production
  • Visual speech

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    Cvejic, E., Kim, J., Davis, C. W., & Gibert, G. (2010). Prosody for the eyes: Quantifying visual prosody using guided principal component analysis. 1433-1436. Paper presented at 11th Annual Conference of the International Speech Communication Association: Spoken Language Processing for All, INTERSPEECH 2010, .