lpcmatlab代码-1D-Triplet-CNN:1D-Triplet-CNN神经网络模型的PyTorch实现在A.Chowdhury和A

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lpc matlab代码一维三重神经网络 1D-Triplet-CNN神经网络模型的PyTorch实现在A.Chowdhury和A.Ross使用1D三重态CNN融合MFCC和LPC功能中对严重降级的音频信号中的说话人进行识别中进行了描述。 研究文章 和,使用严重降级的音频信号中的1D三重态CNN融合MFCC和LPC功能以进行说话人识别,《 IEEE信息取证与安全交易》(2019年)。 IEEE Xplore: 实施细节和要求 该模型是使用Python 3.6在PyTorch 1.2.1中实现的,并且可能与PyTorch和Python的不同版本兼容,但尚未经过测试。 文件中列出了其他要求。 用法 源代码和模型参数 1D-Triplet-CNN模型的源代码可以在子目录中找到,而预训练模型可以在子目录中找到。 数据集 子目录中可使用的预训练模型是根据从获得的Fisher语言语料库的子集进行训练的。 训练数据也因从数据集获得的不同程度的Babble噪声而退化。 训练1D-Triplet-CNN模型 为了按照研究论文所述训练1D-Triplet-CNN模型,请使用子目录中提供的1D-Triple

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