Function inverse_stft

tensorflow/python/ops/signal/spectral_ops.py:157–275

Computes the inverse [Short-time Fourier Transform][stft] of `stfts`. To reconstruct an original waveform, a complimentary window function should be used in inverse_stft. Such a window function can be constructed with tf.signal.inverse_stft_window_fn. Example: ```python frame_length =

(stfts,
                 frame_length,
                 frame_step,
                 fft_length=None,
                 window_fn=window_ops.hann_window,
                 name=None)

@tf_export('signal.inverse_stft')
def inverse_stft(stfts,
                 frame_length,
                 frame_step,
                 fft_length=None,
                 window_fn=window_ops.hann_window,
                 name=None):
  """Computes the inverse [Short-time Fourier Transform][stft] of `stfts`.

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

  Example:

  ```python
  frame_length = 400
  frame_step = 160
  waveform = tf.compat.v1.placeholder(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 in stft, it must be passed to
  inverse_stft_window_fn:

  ```python
  frame_length = 400
  frame_step = 160
  window_fn = functools.partial(window_ops.hamming_window, periodic=True),
  waveform = tf.compat.v1.placeholder(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 GPU-compatible ops and supports gradients.

  Args:
    stfts: A `complex64` `[..., 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.

  Returns:
    A `[..., samples]` `Tensor` of `float32` signals representing the inverse