How to reconstruction audio signal from spectrogram Stack Exchange?
Start with x 0 being a random vector of length of the audio signal. For me a few iterations were sufficient to get a result that sounded alright. The absolute error to the original signal was nevertheless quite high.
What can you do with a reconstructed spectrogram?
You can use the reconstructed spectrogram versus the original spectrogram to design a filter whose magnitude response transforms one spectrogram to the other. You can then apply this filter to the original time domain data, or to the original FFTs for overlap add/save fast convolution filtering.
How is the magnitude of a spectrogram computed?
If the spectrogram was computed as the magnitude of short time fourrier transforms from overlapping windows, then the spectrogram contains implicitly some phase information. The following iterations do the job :
How are phase reconstruction from amplitude spectrograms used?
In speech processing, an amplitude spectrogram is often used for processing, and the corresponding phases are reconstructed from the amplitude spectrogram by using the Griffin-Lim method. However, the Griffin-Lim method causes unnatural artifacts in synthetic speech.
How are amplitude spectrograms used in speech processing?
A variety of speech processing and machine learning-based methods, such as audio source separation and speech enhancement, involve processing an amplitude spectrogram obtained through the short-term Fourier transform (STFT).
Can a reconstructed spectrogram be used as a filter?
Also the generated spectrogram I generated from the reconstructed signal, although showing the same structures in general, had quite different magnitudes. You can use the reconstructed spectrogram versus the original spectrogram to design a filter whose magnitude response transforms one spectrogram to the other.
How to calculate the Mel spectrogram of an audio input?
S = melSpectrogram (audioIn,fs) returns the mel spectrogram of the audio input at sample rate fs. The function treats columns of the input as individual channels.
What happens when windownormalization is set to true in Mel spectrogram?
When WindowNormalization is set to true, the power (or magnitude) in the mel spectrogram is normalized to remove the power (or magnitude) of the time domain Window. Type of filter bank normalization, specified as the comma-separated pair consisting of ‘FilterBankNormalization’ and ‘bandwidth’, ‘area’, or ‘none’.