是的，可以恢复大部分信号并使用例如Griffin-Lim算法(GLA).可以在 librosa 中找到其针对Python的快速"实现.使用方法如下:

Yes, it is possible to recover most of the signal and estimate the phase with e.g. Griffin-Lim Algorithm (GLA). Its "fast" implementation for Python can be found in librosa. Here's how you can use it:

import numpy as np
import librosa

y, sr = librosa.load(librosa.util.example_audio_file(), duration=10)
S = np.abs(librosa.stft(y))
y_inv = librosa.griffinlim(S)

这就是原始和重建的样子:

And that's how the original and reconstruction look like:

默认情况下，该算法会随机初始化相位，然后反复进行正向和反向STFT操作以估计相位.

The algorithm by default randomly initialises the phases and then iterates forward and inverse STFT operations to estimate the phases.

查看您的代码以重构信号，您只需要执行以下操作:

Looking at your code, to reconstruct the signal, you'd just need to do:

import numpy as np

X_inv = librosa.griffinlim(np.abs(X))

这只是一个例子.正如@PaulR所指出的，在您的情况下，您需要从jpeg加载数据(这是有损的！)，然后首先对amplitude_to_db应用逆变换.

It's just an example of course. As pointed out by @PaulR, in your case you'd need to load the data from jpeg (which is lossy!) and then apply inverse transform to amplitude_to_db first.

由于人工神经网络的进步，可以进一步改善算法，尤其是相位估计. 此处是讨论某些增强功能的论文.

The algorithm, especially the phase estimation, can be further improved thanks to advances in artificial neural networks. Here is one paper that discusses some enhancements.