摘要
So far, phonetic features have been the main type of forensic speaker recognition features studied and used in practice. One problem with phonetic forensic speaker recognition features is that they are affected dramatically by the real-world conditions, which results in within-speaker variations and consequently reduces the reliability of forensic speaker cognition results. In this context, supported by Sapir’s description of the structure of speech behavior and discourse information theory, natural conversations are adopted as experiment materials to explore nonphonetic featuresthat are supposed to be less affected by real‑world conditions. The results of experimentsshow that first there exist nonphonetic featuresbesides phonetic features, and what’s more, the nonphonetic features are less affected by real-world conditions as expected.
基金
This paper is one of the outcomes of the“13th Five-Year Plan”Philosophy and Social Science Research Program(GD16CWW02)
the Study of Identification of We-Media Language in Big Data Era,which is directed by Guan Xin and has been approved by Guangdong Planning Office of Philosophy and Social Science in 2016.