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I read about time delay neural network (TDNN) and I am not sure I understood it. From what I read it seems that tdnn works just like one dimensional convolutional neural network (CNN).

What are the differences between the architectures, if they exist?

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I found the answer - there is no difference.

According to the paper "Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks": "Time Delay Neural Networks (TDNNs), also known as one dimensional Convolutional Neural Networks (1-d CNNs)..."

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They are the same, as far as i can see. The name convolution usually applies to spatial not time dimensions, but that is only convention. Wikipedia also links the two.

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    $\begingroup$ In signal processing (e.g. audio or radio) convolution typically implies time dimension. $\endgroup$
    – kylefinn
    Commented Jul 15, 2022 at 18:00

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