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法医深度假冒音频检测使用分段语音功能.

Tianle Yang1, Chengzhe Sun2, Siwei Lyu2

  • 1University at Buffalo, Department of Linguistics, Buffalo, 14260, NY, United States.

Forensic science international
|December 12, 2025
PubMed
概括
此摘要是机器生成的。

这项研究表明,特定的语音声音特征可以有效地检测音频深度假冒,与一般音频特征不同. 为更准确的法医深度假冒检测,提出了一种针对扬声器的新方法.

关键词:
深度假冒音频检测检测 深度假冒音频检测深度假冒演讲演讲法医语音比较法医语音比较概率比率的可能性比率.

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科学领域:

  • 声学语音学的声音学
  • 数字法医学数字法医学
  • 人工智能的人工智能

背景情况:

  • 深度假冒音频对真实性验证构成重大挑战.
  • 目前的深度假冒检测方法通常依赖于全球音频功能.
  • 对深度假冒生成模型来说,复制细粒度的关节性语音特征是很困难的.

研究的目的:

  • 为了研究分段语音声音特征对音频深度假冒检测的有效性.
  • 为了比较细分与全球特征在识别深度假冒方面的表现.
  • 提出和评估一个新的扬声器特定框架,用于深度假冒检测.

主要方法:

  • 对细分语音声音的声学特征的分析.
  • 使用法医语音比较 (FVC) 中常见的特征.
  • 开发和测试一个音箱特定的深度假冒检测框架.

主要成果:

  • 某些细分特征,特别是FVC中使用的特征,在检测音频深度伪造方面是有效的.
  • 全球音频功能在区分深度假冒方面具有有限的价值.
  • 拟议的扬声器特定框架显示了与扬声器独立系统相比的潜在优势.

结论:

  • 分段声学特征为音频深度假冒检测提供了一个有希望的途径,与传统的FVC方法不同.
  • 针对扬声器的特定检测框架对于需要高可解释性和灵敏度的法医应用是有利的.
  • 未来的研究应该专注于改进扬声器特定模型,以进行强大的深度假冒识别.