用于临床应用的可重度控制的病理性文字转化为语音合成
概括
这项研究引入了一种新的病理性语文转化 (TTS) 系统,用于可控制的语音合成. 该系统通过先进的数据增强和架构修改来增强病态语音的自然性和稳定性.
科学领域:
- 语音合成 语音合成
- 病理性语言病理学
- 机器学习 机器学习
背景情况:
- 病态语音合成在控制语音严重程度方面存在挑战.
- 现有的文字转化语音 (TTS) 系统在产生各种病态语音特征方面扎.
- 对于单个发言者的病态语音,生成多重度数据集是很困难的.
研究的目的:
- 开发一种新的病理性文字转化为语音 (TTS) 合成系统,能够控制语音严重程度.
- 为了提高合成病态语音的自然性,可控性和稳定性.
- 为了利用现有的扬声器嵌入式 (x-向量) 进行严重性调节.
主要方法:
- 利用数据增强来创建一个单扬声器多重度训练数据集.
- 采用x向量作为语音严重性控制的条件变量.
- 修改了GradTTS架构,以改善病态语音的持续建模.
主要成果:
- 拟议的GradTTS系统与基线TransformerTTS相比,表现优越.
- 客观和主观评估证实了该系统的有效性.
- 该系统成功生成了更自然,可控制和稳定的病态语音样本.
结论:
- 开发的GradTTS系统提供了对病理性语音严重性的有效控制.
- 整合x向量和架构修改增强了病态TTS的能力.
- 这项工作推进了可控制和自然听起来的病态语音合成领域.
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