【摘要】 本文提出了一种基于最近邻线分类器的新的双端检测器(DTD)。主要的思想是充分地利用特征信息以及用模式识别方法来设计DTD。本文从模式分类的角度分析了二种主要的传统DTD(Geigel和相关DTD)并给出了新的设计方法。一种称为NNL分类器的新的非参数分类器被用来检测双端通话。NNL分类器具有低运算量和优良的性能。用NNL分类器,我们熔合了几种传统的DTD并且避免了存在于大多数传统DTD中的固定阈值带来的问题。因此NNL-DTD在各种条件下是鲁棒的。实验结果也显示出了这个方法比传统方法更有效。更多还原

【Abstract】 This paper presents a novel double-talk detector (DTD) based on a nearest neighbor line (NNL) classifier. The underline idea is to use the feature information sufficiently and to design the DTD with pattern classification method. This paper analyzes 2 main kinds of conventional DTD, Geigel and DTD based on correlation, from the perspective of pattern classification, and then gives a new design method of DTD. A novel nonparametric classifier called NNL classifier is introduced to detect double-talk. NNL classifier has low computation cost and good performance. With NNL classifier, we fuse several conventional DTD and avoid the problem of making a fixed threshold, which exists in most of the conventional DTD. So the NNL-DTD is robust in adverse conditions. Experiments show that the proposed approach is more effective than conventional methods.更多还原