首次量化人类声音的唯一性，证明其在100亿人口中几乎不可能重复。
Human Voice is Unique
- 基于声带生理特征构建声音唯一性评估框架
- 100亿人中两人声音相同概率低于一万亿分之一
- 为语音识别与身份验证系统提供理论依据
声音在越来越多的应用中被用作生物特征，包括说话人识别、验证以及基于声音的人格分析。然而，真正可靠的生物特征必须具备唯一性。本文首次建立了一个客观计算人类声音唯一性的框架。该方法基于统计学原理，选取一系列与发声过程有因果关系、彼此独立且不可推导的声音可测量特征。根据这些变量的量化方式不同，我们得出在100亿人口的世界中，两人拥有相同声音的概率从数千分之一到一千万亿分之一甚至更低。论文还讨论了这一计算结果对语音处理应用设计的影响。
原文摘要 · Abstract (English)
Voice is increasingly being used as a biometric entity in many applications. These range from speaker identification and verification systems to human profiling technologies that attempt to estimate myriad aspects of the speaker's persona from their voice. However, for an entity to be a true biometric identifier, it must be unique. This paper establishes a first framework for calculating the uniqueness of human voice objectively. The approach in this paper is based on statistical considerations that take into account a set of measurable characteristics of the voice signal that bear a causal relationship to the vocal production process, but are not inter-dependent or derivable from each other. Depending on how we quantize these variables, we show that the chances of two people having the same voice in a world populated by 10 billion people range from one in a few thousand, to one in a septillion or less. The paper also discusses the implications of these calculations on the choices made in voice processing applications.
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