Speaker Verification Based on Log-Likelihood Score Normalization

• 作者: Chunyan Liang Shuxin Cao Wei Cao
• 来源期刊: 电脑和通信(英文)
• 学科: 文学
• 关键词: Speaker Verification Score Normalization Log-Likelihood Normalization Zero Normalization Test Normalization
• 年，卷（期）: 2020,（11）
• 页码范围: 80-87
• 页数: 8页
• 分类号: H31

摘要

Due to differences in the distribution of scores for different trials, the performance of a speaker verification system will be seriously diminished if raw scores are directly used for detection with a unified threshold value. As such, the scores must be normalized. To tackle the shortcomings of score normalization methods, we propose a speaker verification system based on log-likelihood normalization (LLN). Without a priori knowledge, LLN increases the separation between scores of target and non-target speaker models, so as to improve score aliasing of “same-speaker” and “different-speaker” trials corresponding to the same test speech, enabling better discrimination and decision capability. The experiment shows that LLN is an effective method of scoring normalization.