如何训练具有不同输入大小的神经网络? [英] How to train a neural network with different size of input?

问题描述

我想用不同的声音训练我的神经网络.但是，每种声音的大小都不同.有谁知道如何训练输入大小不同的神经网络?谢谢.

I want to train my neural network with different sounds. However, the size of each sounds are different. Does anyone know how to train a neural network with different size of input? Thanks.

推荐答案

无法对不同大小的输入进行分类，但是您可以将信号转换为固定大小的特征向量序列(或固定序列的向量)大小的原始声音). 对于声音，我们通常使用MFCC或仅使用声谱图.因此，您需要应用对序列进行操作的方法.它可以是递归神经网络，也可以使用前馈网络，然后以某种方式对每个帧的输出进行后处理.

There is no way to classify inputs of different sizes, but you can transform your signal into a sequence of fixed-size feature vectors (or into a sequence of fixed-size pieces of the original sound). For a sound we usually employ MFCCs or just a spectrogram. Thus, you need to apply methods that operate on sequences. It can be a recurrent neural network, or you can employ a feed-forward network and then post-process its outputs for each frame somehow.

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