Vocal tract cross-distance estimation from real-time MRI using region-of-interest analysis

Adam Lammert, Vikram Ramanarayanan, Michael Proctor, Shrikanth Narayanan

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

24 Citations (Scopus)

Abstract

Real-Time Magnetic Resonance Imaging affords speech articulation data with good spatial and temporal resolution and complete midsagittal views of the moving vocal tract, but also brings many challenges in the domain of image processing and analysis. Region-of-interest analysis has previously been proposed for simple, efficient and robust extraction of linguisticallymeaningful constriction degree information. However, the accuracy of such methods has not been rigorously evaluated, and no method has been proposed to calibrate the pixel intensity values or convert them into absolute measurements of length. This work provides such an evaluation, as well as insights into the placement of regions in the image plane and calibration of the resultant pixel intensity measurements. Measurement errors are shown to be generally at or below the spatial resolution of the imaging protocol with a high degree of consistency across time and overall vocal tract configuration, validating the utility of this method of image analysis.

Original languageEnglish
Title of host publicationProceedings of the Annual Conference of the International Speech Communication Association
Place of PublicationBaixas
PublisherInternational Speech Communication Association (ISCA)
Pages959-962
Number of pages4
Publication statusPublished - 2013
Externally publishedYes
EventInterspeech 2013: 14 Annual Conference of the International Speech Communication Association - Lyon, France
Duration: 25 Aug 201329 Aug 2013

Conference

ConferenceInterspeech 2013
CountryFrance
CityLyon
Period25/08/1329/08/13

Keywords

  • Analysis tools
  • Real-time MRI
  • Speech production data
  • Vocal tract area functions

Fingerprint

Dive into the research topics of 'Vocal tract cross-distance estimation from real-time MRI using region-of-interest analysis'. Together they form a unique fingerprint.

Cite this