The support vector machine based speaker verification models are trained on the enrolled speaker and the background model.

支持向量机用作说话人确认模型来训练目标说话人和背景说话人的语音数据。

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Compared with multivariate statistics and artificial neural networks, support vector machine based on structure risk minimization has better classification performance.

与统计分析和神经网络相比，基于结构风险最小的支持向量机有更好的分类性能。

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In order to solve the problem, support vector machine based on weighted feature is proposed in this paper.

为了解决这个问题，本文提出了一种基于特征加权的支持向量回归机。

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