使用权重线性预测估计索普拉诺唱歌的元音的形式频率
Eduardo Barrientos1, Edson Cataldo1
1Postgraduate Program in Electrical and Telecommunications Engineering (PPGEET), R. Passo da Pátria, Niterói, RJ, Brazil.
Journal of voice : official journal of the Voice Foundation
|November 24, 2023
概括
一种新的方法,适应高音唱歌声的加权线性预测 (WLP-HPSV),准确地估计了索普拉诺歌唱中的形式频率. 这种技术优于传统方法,在各种音调中提供了强大的声乐分析.
科学领域:
- 声学 声学 在声学方面
- 语音科学 语言科学
- 生物声学是一种生物声学.
背景情况:
- 准确的形式频率估计对于理解语音产生至关重要.
- 高调的歌声对传统的光谱分析方法构成独特的挑战.
- 像线性预测编码 (LPC) 这样的现有方法可能会与歌唱元音的复杂性作斗争.
研究的目的:
- 引入和评估一种新的方法,适应高调歌声的加权线性预测 (WLP-HPSV),用于精确的形式频率估计.
- 将WLP-HPSV的性能与已建立的线性预测编码 (LPC) 方法进行比较.
- 为了研究唱歌中音调和声道/状管特征之间的关系.
主要方法:
- 开发了适应高音唱歌声 (WLP-HPSV) 的加权线性预测方法.
- 在WLP分析框架内的集成零频过 (ZFF) 技术.
- 评估WLP-HPSV使用合成 /u/母音和自然 /a/和 /u/歌词母音.
- 将WLP-HPSV结果与从LPC方法获得的结果进行比较.
主要成果:
- 与LPC相比,WLP-HPSV在准确捕捉光谱特征方面表现出卓越的性能.
- 该方法准确地估计了合成和自然唱歌元音的形式频率.
- 观察到近闭阶段 (QCP) 参数与音调的变化,表明声道和喉相互作用.
- WLP-HPSV在估计各种音高的形式频率方面表现出强大.
结论:
- WLP-HPSV是一种高效的方法,用于在高调的唱歌声中准确估计形式频率.
- WLP-HPSV方法比传统的LPC分析提供了更好的稳定性和准确性.
- 这项研究提供了对高音,声道配置和高源特征在高唱歌唱期间的动态关系的见解.
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