| 摘要: |
| 提出了一种用于文本相关说说话人确认技术的i-向量提取方法和L-向量表示.一段用于注册或识别的语音可以用i-向量和L-向量联合表示.同时提出了一种改进的用于支持向量机(SVM)后端分类的核函数,改进的核函数可以同时区分说话人身份的差异和文本内容的差异.在RSR 2015语料集合1和集合2上验证系统的性能,实验结果显示改进的算法相对于传统的i-向量系统的基线能提高至多30%的识别率. |
| 关键词: 文本相关说话人识别 i-向量 L-向量 余弦核函数 |
| DOI： |
| 分类号: |
| 基金项目:the National Natural Science Foundation of China (NSFC) under Grant (61271349,61371147,11433002),and Shanghai Jiao Tong University joint research fund for Biomedical Engineering under (YG2012ZD04) |
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| A novel L-vector representation and improved cosine distance kernel for Text-dependent Speaker Verification |
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LI Wei1, YOU Hanxu1, ZHU Jie1, CHEN Ning2
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1.School of Electronic Information and Electrical Engineering,Shanghai Jiao Tong University;2.School of Information Science and Engineering,East China University of Science and Technology
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| Abstract: |
| A text-dependent i-vector extraction scheme and a lexicon-based binary vector (L-vector) representation are proposed to improve the performance of text-dependent speaker verification.An utterance used for enrollment or test is represented by these two vectors.An improved cosine distance kernel combining i-vector and L-vector is constructed to discriminate both speaker identity and lexical (or text) diversity with back-end support vector machine(SVM).Experiments are conducted on RSR 2015 Corpus part 1 and part 2.The results indicate that at most 30% improvement can be obtained compared with traditional i-vector baseline. |
| Key words: text-dependent speaker verification i-vector L-vector cosine distance kernel |
