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Updated: Jul 18, 2025

fMRI Mapping of Brain Activity Associated with the Vocal Production of Consonant and Dissonant Intervals

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Published on: May 23, 2017

Quantifying Velopharyngeal Motion Variation in Speech Sound Production Using an Audio-Informed Dynamic MRI Atlas.

Fangxu Xing¹, Riwei Jin², Imani Gilbert³

¹Dept. Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, US 02114.

Proceedings of Spie--The International Society for Optical Engineering

|August 25, 2023

Summary

This summary is machine-generated.

This study introduces a novel method to visualize subtle velopharyngeal (VP) motion variations during speech using dynamic MRI. The technique identifies unique VP deformation patterns across individuals, aiding in understanding speech production differences.

Keywords:

Motion PCA atlas audio waveform dynamic MRI speech velopharynx

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Area of Science:

Medical Imaging
Speech Science
Biomechanical Analysis

Background:

Dynamic magnetic resonance imaging (MRI) enables real-time capture of human velopharyngeal (VP) deformations during speech.
Speech motion atlases allow for group analysis of spatially and temporally aligned VP motion data.
Identifying subtle variations in VP deformation patterns across subjects presents a significant analytical challenge.

Purpose of the Study:

To develop and validate a method for computing and visualizing subtle VP deformation variation patterns.
To extract unique, pronunciation-specific VP motion patterns from high-dimensional dynamic MRI data.
To correlate audio features with spatial VP motion variations for enhanced speech analysis.

Main Methods:

Utilized principal component analysis (PCA) on dynamic motion fields within an atlas space to identify deformation patterns.
Integrated real-time audio recordings to pinpoint key speech time frames with maximum variation.
Warped subject-specific motion fields into a common atlas space for quantitative analysis of variations.

Main Results:

Successfully computed and visualized subtle VP motion differences across twelve healthy subjects.
Identified principal components that represent key variations in VP deformation patterns.
Demonstrated the ability to reveal pronunciation-specific VP motion characteristics.

Conclusions:

The developed method effectively visualizes subtle VP motion variations, enabling quantitative analysis of speech-related deformations.
This approach aids in distinguishing individual differences in velopharyngeal kinematics during speech.
The findings contribute to a deeper understanding of the biomechanics of speech production.