发言者说"a souk"使用反向阿特拉斯舌头建模的发言者之间的运动控制相似性
Ursa Maity1, Fangxu Xing2, Jerry Prince3
1School of Biomedical Engineering, University of British Columbia, Canada.
Interspeech
|December 18, 2023
概括
这项研究开发了舌头的有限元模型 (FEM),以预测语音期间的肌肉激活. 研究结果显示,说话者在表达"a souk"的舌头运动策略中存在显著的变化.
科学领域:
- 生物力学 生物力学
- 语音科学 语言科学
- 计算建模 计算建模
背景情况:
- 有限元模型 (FEM) 对于语音研究至关重要,它可以从成像数据中间接分析内部肌肉力量.
- 以前的研究已经利用FEM来理解舌头机制,但直接预测语音期间肌肉激活仍然具有挑战性.
研究的目的:
- 从MRI数据开发一个统一的六边形FEM的舌头地图.
- 通过反向的舌头地图模型,调查语言声音"a souk"的发音过程中舌头运动策略的共同点和变异.
- 预测肌肉激活和分析扬声器特定差异.
主要方法:
- 从一个健康的舌头图谱的磁共振成像 (MRI) 数据构建一个均的六面体FEM.
- 驱动FEM与5个扬声器的反向内部舌头组织动力学,执行语音任务"a souk".
- 扬声器数据的时间对齐和变形进入亚特拉斯空间,用于肌肉激活预测.
- 使用动态时间曲线函数计算相似度指数来比较肌肉激活模式.
主要成果:
- 在五位演讲者中观察到估计肌肉激活的变化.
- 两位发言者在大多数舌头肌肉方面表现出高相似度指数 (> 0.9) 与参考发言者.
- 另外两位演讲者与参考演讲者相比,相似度指数较低 (<0.7).
- FEM实现了相对运动跟踪误差低于2%的相对运动跟踪误差.
结论:
- 开发的FEM为语音研究提供了一个有前途的工具,可以预测肌肉激活.
- 在用于表达"a souk"的运动策略中存在显著的语音间变化.
- 该模型的准确性表明它对进一步研究语音生产机制的有用性.
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