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Computer Aided Co-articulation Model Based on Magnetic Resonance Images

机译:基于磁共振图像的计算机辅助共关节模型

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Magnetic Resonance Imaging technique makes it possible to measure the motion of tissues in our body organs more clearly than other medical imaging techniques. The aim of this paper is to build a co-articulatory model based on Magnetic Resonance Images (MRI). This work is a blend of various emerging technologies such as computer vision based visualization technologies, cognitive science, medical science, speech recognition. The sounds of human speech can be combined in many ways, and the associated articulator movements vary as the kinematic context changes. This kinematic variation, known as co-articulation is one of the most pervasive characteristics of speech production. Visualization of co-articulatory effects involved in the speech production will lead to a better understanding of the speech production process. MRI video obtained (from the subject AR) during the co-articulation of Tamil phonemes has been incorporated as input and processed to envision the movements of the key articulators involved in the speech production process. The Region of Interest for the articulators such as jaw, tongue, lower lip, and upper lip were obtained. The motion parameters for individual articulators and their positions in subsequent frames are estimated using Block matching algorithm. Estimated motion parameters are visualised and then reproduced. This system can act as an efficient tool to control the place of articulation visually to aid second language learners and also for the people suffering from mis-articulation to learn the correct method of articulation.
机译:磁共振成像技术使得可以比其他医学成像技术更清楚地测量我们的身体器官中组织的运动。本文的目的是建立基于磁共振图像(MRI)的共同关节模型。这项工作是各种新兴技术的混合,如计算机视觉的可视化技术,认知科学,医学,语音识别。人类语音的声音可以在许多方面组合,并且相关的铰接器运动随着运动背景的变化而变化。这种运动变异,称为共同关注是语音生产最普遍的特征之一。演讲生产中涉及的共同剖视效应的可视化将导致对语音生产过程的更好理解。在泰米尔音素的共同关节期间获得的MRI视频已被纳入输入并加工以设想涉及语音生产过程中涉及的关键清晰度的运动。获得钳口,舌头,下唇和上唇等铰接器的感兴趣区域。使用块匹配算法估计各个铰接器的运动参数及其在后续帧中的位置。可视化估计的运动参数,然后再现。该系统可以充当一个有效的工具,以便在视觉上控制铰接地点,以帮助第二语言学习者,并为患有错误清晰度的人来学习正确的阐明方法。

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