系统梳理语音口音转换的技术演进与社会语言学挑战。
Accent Conversion: A Problem-Driven Survey of Sociolinguistic and Technical Constraints
- 从信号处理到神经网络,方法逐步实现无参考转换。
- 强调口音改变与说话人身份保持间的平衡难题。
- 适合语音合成、跨文化沟通研究者参考。
口音转换随着提升全球跨文化沟通需求而迅速发展。本综述回顾了口音转换方法的演进,分析其如何应对数据对齐、表征解耦和资源稀缺等核心挑战。从早期基于规则的数字信号处理方法(如谱图调节和共振峰分析)到现代无需参考的神经架构,技术不断进步。同时,论文将口音转换置于语言学基础中,探讨不同应用场景对口音修改与说话人身份保留之间权衡的影响。此外,综述总结了常用语音数据集与评估方法,指出现有持续挑战,并提出未来研究方向,以实现更可控、感知一致的口音转换。
原文摘要 · Abstract (English)
Accent conversion has rapidly progressed alongside growing interest in improving global cross-cultural communication. This survey presents an overview of the evolution of accent conversion methodologies, analyzing how the field has developed in response to fundamental challenges related to data alignment, representation disentanglement, and resource scarcity. We trace the progression from early rule-based digital signal processing approaches such as spectral manipulation and formant-based analysis to modern neural architectures capable of flexible and reference-free accent transformation. In addition, the survey situates accent conversion within its linguistic foundations and examines how different application requirements impose varying constraints on the balance between accent modification and speaker identity preservation. Finally, it reviews commonly used speech datasets and evaluation methodologies, identifies persistent challenges, and outlines directions for future research aimed at achieving more controllable and perceptually consistent accent conversion.
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