离散语音令牌的最新进展:一篇回顾
IEEE transactions on pattern analysis and machine intelligence
|December 12, 2025
概括
本次调查探讨了离散语音令牌,这是大型语言模型 (LLM) 的关键技术. 它对这些令牌进行了分类,并检查了它们的优势,局限性以及语音生成的未来研究方向.
科学领域:
- 人工智能的人工智能
- 自然语言处理自然语言处理.
- 语音技术 语言技术
背景情况:
- 大型语言模型 (LLM) 刺激了语音生成的进步.
- 离散语音令牌为LLMs提供高效兼容的语音表示.
- 目前的研究将离散的语音令牌分为声学和语义类别.
研究的目的:
- 系统地综合分类学和离散语音标记化的创新.
- 批判性地检查声学和语义令牌范式的优势和局限性.
- 提供实验性比较,并确定未来的研究方向.
主要方法:
- 系统的文献审查和综合离散语音标记化研究.
- 现有的离散语音令牌方法的分类.
- 不同的代币类型的实验比较.
主要成果:
- 离散的语音令牌对于将语音整合到LLM架构中至关重要.
- 声学和语义令牌代表着具有独特优缺点的不同方法.
- 实验性比较突出显示了跨代币类型的性能差异.
结论:
- 离散语音代币是LLMs中现代语音生成的基础.
- 需要进一步的研究来应对挑战,并优化代币设计和应用.
- 这项调查提供了关于语音代币化技术未来进步的见解.
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