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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发音模型

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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:磁共振成像技术比其他医学成像技术可以更清晰地测量人体器官组织的运动。本文的目的是建立基于磁共振图像(MRI)的共发音模型。这项工作融合了各种新兴技术,例如基于计算机视觉的可视化技术,认知科学,医学和语音识别。人类语音的声音可以通过多种方式组合,并且随着运动环境的变化,相关的咬合架运动也会发生变化。这种运动学上的变化,称为共同发音,是语音产生的最普遍特征之一。可视化语音生成中涉及的共同发音效果将有助于更好地理解语音生成过程。在泰米尔语音素的共同发音期间获得的(从对象AR获得的)MRI视频已作为输入并进行了处理,以预想参与语音生成过程的关键发音器的运动。获得了诸如下颌,舌头,下唇和上唇之类的咬合架的感兴趣区域。使用块匹配算法估计各个咬合架的运动参数及其在后续帧中的位置。估计的运动参数将被可视化,然后进行再现。该系统可以作为一种有效的工具,以视觉方式控制发音的位置,以帮助第二语言学习者,也可以帮助遭受发音错误的人们学习正确的发音方法。

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