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Use of Support Vector Machines through Linear-Polynomial (LP) Kernel for Speech Recognition

机译:支持向量机通过线性多项式(LP)内核用于语音识别

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摘要

The kernel functions are playing a very important role in machine learning. In this paper, the speech recognition problem is considered as a machine learning problem. The new kernel function called Linear-Polynomial kernel (LP) used to design the support vector machines for speech recognition for improving the generalization performance of speech recognition. The LP kernel performance is very good as compared to linear kernel and polynomial kernel and has improved the generalization performance ability of the speech recognition system. The One-versus-One approach is used for improving the systems efficiency.
机译:内核功能在机器学习中起着非常重要的作用。在本文中,语音识别问题被视为机器学习问题。新的称为线性多项式内核(LP)的内核函数用于设计用于语音识别的支持向量机,以提高语音识别的泛化性能。与线性核和多项式核相比,LP核的性能非常好,并且提高了语音识别系统的泛化性能。一对一方法用于提高系统效率。

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