Link Prediction Methods for Generating Speaker Content Graphs.

机译：生成说话人内容图的链接预测方法。

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摘要

In a speaker content graph, vertices represent speech signals and edges represent speaker similarity. Link prediction methods calculate which potential edges are most likely to connect vertices from the same speaker; those edges are included in the generated speaker content graph. Since a variety of speaker recognition tasks can be performed on a content graph, we provide a set of metrics for evaluating the graph’s quality independently of any recognition task. We then describe novel global and incremental algorithms for constructing accurate speaker content graphs that outperform the existing k nearest neighbors link prediction method. We evaluate these algorithms on a NIST speaker recognition corpus.

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作者
Greenfield, K.; Campbell, W. M.;
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年度 2015
页码 1-5
总页数 5
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
Speaker recognition; Network theory; Link prediction; Algorithms; Vector methods; Graph construction; Speaker content; Content graphs;

机译：说话人识别;网络理论;链接预测;算法;矢量方法;图形构造;说话人内容;内容图;

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4. Link prediction methods for generating speaker content graphs [C] . Greenfield K., Campbell W.M. IEEE International Conference on Acoustics, Speech and Signal Processing . 2013

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6. Experimental identification of specificity determinants in the domain linker of a LacI/GalR protein: Bioinformatics-based predictions generate true positives and false negatives [O] . Sarah Meinhardt, Liskin Swint-Kruse -1

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7. LINK PREDICTION METHODS FOR GENERATING SPEAKER CONTENT GRAPHS [O] . K. Greenfield, W. M. Campbell 2015

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8. Query-by-Example Using Speaker Content Graphs. [R] . Campbell, W. M., Singer, E. 2016

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Link Prediction Methods for Generating Speaker Content Graphs.

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