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Abstract #0139

Support Vector Machines can Decode Speech Patterns from High Speed Dynamic Spiral FLASH Images of the Mouth

Stephen LaConte1, Jonathan Lisinski1, Bradley Sutton2

1School of Biomedical Engineering & Sciences, Virginia Tech, Blacksburg, VA, USA; 2Bioengineering, University of Illinois, Urbana-Champaign, Urbana, IL, USA

We imaged the oropharyngeal cavity at 15.8 frames per second using a recently developed multi-shot, field corrected, dynamic spiral FLASH sequence. We explored the extent to which speech-related information is captured by this sequence. During imaging, we asked a subject to perform a visually guided speech task, consisting of alternating 20 sec. blocks of slow and fast counting. Support vector machine analysis used the soft palate, lips, and tongue and resulted in 88% prediction accuracy, demonstrating that it is possible to classify individual frames as either fast or slow speech. This achievement has potential applications in speech therapy and diagnosis.