论文标题
使用MLP分类器和LPCC代码簿的扬声器识别
Speaker recognition with a MLP classifier and LPCC codebook
论文作者
论文摘要
本文使用两种方法之间的线性组合，仅将MLP分类器和LPCC代码手册的扬声器识别率提高。在模拟中，我们获得了32个矢量的LPCC代码书的4.7％和128个矢量的代码书（错误率从3.68％下降到2.1％）。另外，我们提出了一种有效的算法，该算法将LPCC-VQ系统的计算复杂性降低了4倍。
This paper improves the speaker recognition rates of a MLP classifier and LPCC codebook alone, using a linear combination between both methods. In simulations we have obtained an improvement of 4.7% over a LPCC codebook of 32 vectors and 1.5% for a codebook of 128 vectors (error rate drops from 3.68% to 2.1%). Also we propose an efficient algorithm that reduces the computational complexity of the LPCC-VQ system by a factor of 4.
