基于TDNN的说话人识别

1993 (25th) Southeastern Symposium on System Theory Pub Date : 1993-03-07 DOI:10.1109/SSST.1993.522810

G. L. Berger, J. Gowdy

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引用次数: 1

摘要

考虑了一种时空网络——时滞神经网络(TDNN)。因为TDNN是时移不变的，输入模式不需要对齐。此外，TDNN在其映射过程中使用了时间信息。实验结果表明，基于tdnn的说话人识别优于不使用时间信息的基于加权距离度量的说话人识别系统。

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TDNN based speaker identification

A spatio-temporal network the time delay neural network (TDNN) is considered. Because the TDNN is time-shift invariant, input patterns do not need to be aligned. Also, the TDNN uses temporal information in its mapping process. Experimental results show that a TDNN-based speaker identification outperforms a weighted-distance-measure-based speaker identification system that does not use temporal information.

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1993 (25th) Southeastern Symposium on System Theory

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