转音器:通过基于IPA的语音调整进行跨语言的唱歌语音合成
Chen Shen1, Lu Zhao1, Cejin Fu1
1College of Computer and Information Engineering (College of Artificial Intelligence), Nanjing Tech University, Nanjing 211816, China.
Sensors (Basel, Switzerland)
|July 12, 2025
概括
通过使用国际音联字母 (IPA) 来进行跨语言的概括,Transinger 增强了歌声合成 (SVS). 这种新的方法改善了未见语言的发音建模,推进了SVS的能力.
科学领域:
- 人工智能的人工智能
- 语音技术 语言技术
- 计算语言学 计算语言学
背景情况:
- 歌声合成 (SVS) 面临着全球语言多样性带来的挑战.
- 分碎的,特定于语言的语音编码阻碍了SVS中的统一语音建模.
- 现有的SVS研究缺乏跨语言概括的探索.
研究的目的:
- 开发一种跨语言的歌声合成框架,克服语言障碍.
- 改进SVS模型中的语音表示和概括能力.
- 为未明确包含在培训数据中的语言启用SVS.
主要方法:
- 使用国际语音字母 (IPA) 创建了四种语言的数据集,以实现一致的语音表示.
- 提出了一种新的方法,将IPA音符分解为字母和双重写符,以便更深入地学习发音规则.
- 介绍了Transinger,这是一个跨语言合成框架,集成了Conformer和RVQ技术.
- 开发了一个动态的IPA适应策略,用于将学习表达式应用于未见的语言.
主要成果:
- 与最先进的方法相比,Transinger在跨语言概括方面取得了显著的改进.
- 客观和主观实验证实了拟议方法的有效性.
- 该方法实现了卓越的跨语言合成性能,即使对于培训期间未见过的语言.
结论:
- 多语言对齐表示增强SVS模型学习的有效性和稳定性.
- 将 IPA 音符分解为字母和对称符号可以改善发音学习和概括.
- "Transinger"代表了跨语言歌唱语音合成的突破.
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