Selection of optimal vocal tract regions using real-time magnetic resonance imaging for robust voice activity detection

Abhay Prasad, Prasanta Kumar Ghosh, Shrikanth S. Narayanan

Research output: Contribution to journalConference article

Abstract

Real time magnetic resonance imaging (rtMRI) enables direct video capture of the moving vocal tract concurrent with audio signal providing valuable data for speech research. We consider a multimodal approach to voice activity detection (VAD) in the rtMRI recording that uses audio signal as well as MRI image sequence. The degraded quality of the audio recorded in the scanner motivates this multimodal scheme for robust VAD. Optimal regions in the MRI image are selected for performing VAD with a novel algorithm. VAD experiments using rtMRI data of two male and two female subjects show that VAD performance using optimally selected regions from MRI images is comparable to that using only audio signal. The optimal regions turn out to be parts of jaw, velum, glottis and lips. VAD performance using audio signal and MRI image sequence together is found to be significantly better (∼14% absolute improvement in VAD accuracy) than that using the audio only when the audio is contaminated with additive noise at low SNR.

Original languageEnglish
Pages (from-to)1539-1543
Number of pages5
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Publication statusPublished - 01-01-2014
Externally publishedYes
Event15th Annual Conference of the International Speech Communication Association: Celebrating the Diversity of Spoken Languages, INTERSPEECH 2014 - Singapore, Singapore
Duration: 14-09-201418-09-2014

All Science Journal Classification (ASJC) codes

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

Fingerprint Dive into the research topics of 'Selection of optimal vocal tract regions using real-time magnetic resonance imaging for robust voice activity detection'. Together they form a unique fingerprint.

  • Cite this