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InverseSpectrogram—Wolfram Language Documentation

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• See Also
  • InverseShortTimeFourier
  • ShortTimeFourier
  • SpectrogramArray
  • Spectrogram
  • Audio
  • PeriodogramArray
  • Fourier
• Related Guides
  • Fourier Analysis
  • Signal Visualization & Analysis
  • Audio Analysis
  • Audio Representation

InverseSpectrogram[img]

reconstructs the signal, assuming that the image img is the magnitude spectrogram.

InverseSpectrogram[input,n]

assumes the spectrogram data was computed with partitions of length n.

InverseSpectrogram[input,n,d,wfun]

assumes a smoothing window wfun was applied to each partition.

• InverseSpectrogram approximates an inverse of the magnitude spectrogram.
• To compute the short-time Fourier transform of lists and audio signals, use ShortTimeFourier.
• InverseSpectrogram assumes that real matrix input is a magnitude spectrogram without the redundant part. This means that the window size used was 2(size-1), where size is the second dimension of the input matrix.
• The inverse spectrogram can be computed from the spectrogram if the offset d is smaller than half the size of the partition length n.
• The following options can be given:
• Possible method settings include:
• Automatic uses automatic method "GriffinLim" iteratively approximates the phase "SPSI" uses single-pass spectrogram inversion "Hybrid" uses the SPSI as the inital phase for Griffin–Lim
• The "Hybrid" method is used by default.

Generate an audio signal, assuming a cellular automaton evolution to be the magnitude spectrum:

Reconstruct a signal from a magnitude spectrum:

Construct an Audio object from an Image:

Compute the spectrogram of the resulting signal:

The partition size must match the value inferred from the input data:

The inferred partition size is 2×(size-1), where size is the second dimension of the input matrix:

By default, the partition offset is of the inferred partition size:

Specify a different partition offset:

Specify a smoothing window:

Use the MaxIterations option to control the quality of the result and the speed of the operation:

The "Griffin-Lim" method uses an iterative algorithm to approximate the original signal:

The "SPSI" method approximates the signal in a non-iterative way, which is relatively fast:

The "Hybrid" method uses the result of the "SPSI" method as the starting guess for iterative method "Griffin-Lim", which may converge faster:

Reconstruct an Audio object from its magnitude spectrum:

Construct an Audio object from image data:

Convert the image to grayscale and rotate appropriately:

Reconstruct the signal with the assumption that the image was its spectrogram:

Compute the spectrogram of the resulting signal:

Compute the spectrogram of a signal and its approximate inverse:

Compute the short-time Fourier transform:

Discard the redundant part and take the absolute value to get the magnitude spectrogram:

Use InverseSpectrogram to compute the approximated inverse of the spectrogram:

The partition size must match the value inferred for the input data:

The inferred partition size is 2×(size-1), where size is the second dimension of the input matrix:

Signal reconstruction cannot be done with other partition sizes:

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