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基于MFCC和LPCC的说话人识别

于 2022-12-10 发布 文件大小:259.29 kB
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MFCC 参数和 LPCC 参数是说话人识别中两种最常用的特征参数,研究了 MFCC 和 LPCC 参数提取的算法原理及差分倒谱参数的提取方法,采用MFCC、LPCC 及其一阶、二阶差分作为特征参数,通过 k 均值算法与三层BP 神经网络来进行说话人识别。实验结果表明,该方法可以有效提高识别率,同时也验证 MFCC 参数的鲁棒性优于 LPCC 参数

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