Facial (e.g., lips and jaw) movements can provide important information for the assessment, diagnosis and treatment of motor speech disorders. However, due to the high costs of the instrumentation used to record speech movements, such information is typically limited to research studies. With the recent development of depth sensors and efficient algorithms for facial tracking, clinical applications of this technology may be possible. Although lip tracking methods have been validated in the past, jaw tracking remains a challenge. In this study, we assessed the accuracy of tracking jaw movements with a video-based system composed of a face tracker and a depth sensor, specifically developed for short range applications (Intel® RealSense™ SR300). The assessment was performed on healthy subjects during speech and nonspeech tasks. Preliminary results showed that jaw movements can be tracked with reasonable accuracy (RMSE≈2mm), with better performance for slow movements. Further tests are needed in order to improve the performance of these systems and develop accurate methodologies that can reveal subtle changes in jaw movements for the assessment and treatment of motor speech disorders.
Video-based tracking of jaw movements during speech: Preliminary results and future directions / Bandini, A.; Namasivayam, A.; Yunusova, Y.. - 2017-:(2017), pp. 689-693. ( 18th Annual Conference of the International Speech Communication Association, INTERSPEECH 2017 swe 2017) [10.21437/Interspeech.2017-1371].
Video-based tracking of jaw movements during speech: Preliminary results and future directions
Bandini A.;
2017
Abstract
Facial (e.g., lips and jaw) movements can provide important information for the assessment, diagnosis and treatment of motor speech disorders. However, due to the high costs of the instrumentation used to record speech movements, such information is typically limited to research studies. With the recent development of depth sensors and efficient algorithms for facial tracking, clinical applications of this technology may be possible. Although lip tracking methods have been validated in the past, jaw tracking remains a challenge. In this study, we assessed the accuracy of tracking jaw movements with a video-based system composed of a face tracker and a depth sensor, specifically developed for short range applications (Intel® RealSense™ SR300). The assessment was performed on healthy subjects during speech and nonspeech tasks. Preliminary results showed that jaw movements can be tracked with reasonable accuracy (RMSE≈2mm), with better performance for slow movements. Further tests are needed in order to improve the performance of these systems and develop accurate methodologies that can reveal subtle changes in jaw movements for the assessment and treatment of motor speech disorders.| File | Dimensione | Formato | |
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