解码舌头的舞蹈:以模型为基础的学习方法,用于共同articulationa中的语音目标)
Jianguo Wei1, Guochen Bai1, Wenhuan Lu1
1College of Intelligence and Computing, Tianjin University, Tianjin 300000, China.
The Journal of the Acoustical Society of America
|October 14, 2024
概括
一个新的语音模型揭示了舌头.
科学领域:
- 语音科学 语言科学
- 语言学的语言学.
- 生物物理学的生物物理.
背景情况:
- 了解语音产生机制对于推进语音合成和治疗至关重要.
- 电磁关节学 (EMA) 提供了关于在讲话时舌头运动的宝贵数据.
- 现有的模型往往简化了表达手势的复杂相互作用.
研究的目的:
- 根据EMA数据开发一种基于语音制作的新型模型.
- 阐明舌头背部和尖端在发音中的不同作用.
- 改进对共同关节现象的建模,特别是预测和转移.
主要方法:
- 使用来自EMA数据库的平均频率组件创建了一个模型.
- 采用了包括统计估计和改进在内的两阶段优化过程.
- 该模型的生理基础是通过关节洞察得到的信息.
主要成果:
- 舌头背部作为载波,而舌头尖作为调制信号.
- 该模型准确地描绘了携带和预期的协同articulation.
- 对于每种音名,我们发现了独特的语音目标,平均误差为0.18厘米.
结论:
- 开发的模型提供了一个细微的理解在语音规划表达力学动态.
- 这些发现提供了对虚拟目标形成的见解,并增强了语音合成能力.
- 模型的准确性通过实证数据和听力测试来验证.
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