tf.signal.inverse_stft

Computes the inverse Short-time Fourier Transform of stfts.

To reconstruct an original waveform, a complementary window function should be used with inverse_stft. Such a window function can be constructed with tf.signal.inverse_stft_window_fn. Example:

frame_length = 400 frame_step = 160 waveform = tf.random.normal(dtype=tf.float32, shape=[1000]) stft = tf.signal.stft(waveform, frame_length, frame_step) inverse_stft = tf.signal.inverse_stft( stft, frame_length, frame_step, window_fn=tf.signal.inverse_stft_window_fn(frame_step)) 

If a custom window_fn is used with tf.signal.stft, it must be passed to tf.signal.inverse_stft_window_fn:

frame_length = 400 frame_step = 160 window_fn = tf.signal.hamming_window waveform = tf.random.normal(dtype=tf.float32, shape=[1000]) stft = tf.signal.stft( waveform, frame_length, frame_step, window_fn=window_fn) inverse_stft = tf.signal.inverse_stft( stft, frame_length, frame_step, window_fn=tf.signal.inverse_stft_window_fn( frame_step, forward_window_fn=window_fn)) 

Implemented with TPU/GPU-compatible ops and supports gradients.

stfts A complex64/complex128 [..., frames, fft_unique_bins] Tensor of STFT bins representing a batch of fft_length-point STFTs where fft_unique_bins is fft_length // 2 + 1
frame_length An integer scalar Tensor. The window length in samples.
frame_step An integer scalar Tensor. The number of samples to step.
fft_length An integer scalar Tensor. The size of the FFT that produced stfts. If not provided, uses the smallest power of 2 enclosing frame_length.
window_fn A callable that takes a window length and a dtype keyword argument and returns a [window_length] Tensor of samples in the provided datatype. If set to None, no windowing is used.
name An optional name for the operation.

A [..., samples] Tensor of float32/float64 signals representing the inverse STFT for each input STFT in stfts.

ValueError If stfts is not at least rank 2, frame_length is not scalar, frame_step is not scalar, or fft_length is not scalar.