在唱歌和说话语音类型的语音类型的分类中,可调整的Q因子波形变换基于特征
Kiran Reddy Mittapalle1, Paavo Alku1
1Department of Information and Communications Engineering, Aalto University, Espoo 02150, Finland.
Journal of voice : official journal of the Voice Foundation
|December 1, 2024
概括
这项研究引入了一种使用可调的Q系波量变换 (TQWT) 来分类语音发音类型的新方法. 基于TQWT的特征显著提高了在唱歌和说话声音中区分呼吸,中性和压力声调的准确性.
科学领域:
- 声学语音学的声音学.
- 信号处理 信号处理
- 机器学习是机器学习.
背景情况:
- 声调,使用喉和呼吸系统产生可听到的声音,允许各种声音类型,如呼吸,中性和压力.
- 这些音调类型在唱歌和说话中都至关重要,影响声质和沟通.
研究的目的:
- 提出和评估一种新的特征提取方法来分类发音类型.
- 评估可调整的Q因子波波变换 (TQWT) 特性在区分呼吸,中性和压力声调之间的有效性.
主要方法:
- 语音信号被分解成子频段使用可调的Q因子波量变换 (TQWT).
- 对每个子频段计算了Shannon波量.
- 使用这些值训练了一个前神经网络来分类发音类型.
主要成果:
- 拟议的基于TQWT的功能与现有的六个最先进的功能相比,表现出了更高的性能.
- 该方法实现了高分类准确率:91%的歌声和82%的说话声音.
- TQWT的特点有效地区分了呼吸,中性和压力语音类型.
结论:
- 可调整的Q因子波波变换 (TQWT) 提供了有效的功能,用于发音类型的分类.
- 这种方法在歌唱和说话应用中准确识别不同的声音品质方面取得了重大进展.
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