Add kaiser window support to resampling #1509
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carolineechen
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torchaudio/functional/functional.py
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| rolloff: float): | ||
| rolloff: float, | ||
| resampling_method: str, | ||
| beta: float = 6.): |
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According to https://numpy.org/doc/stable/reference/generated/numpy.kaiser.html, a value of 6 is similar to a Hanning window shape (used for sinc_interpolation), but I'm open to other default values as well. Resampy uses ~8.55 for their kaiser_fast and ~14.77 for kaiser_best.
carolineechen
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| @@ -1352,15 +1354,20 @@ def _get_sinc_resample_kernel( | |||
| # they will have a lot of almost zero values to the left or to the right... | |||
| # There is probably a way to evaluate those filters more efficiently, but this is kept for | |||
| # future work. | |||
| idx = torch.arange(-width, width + orig_freq) | |||
| idx = torch.arange(-width, width + orig_freq, dtype=torch.float64) | |||
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through running separate scripts, I realized that #1499 introduced rounding errors if waveform dtype was greater than float32. adding dtype=float64 here to retain implementation accuracy from the prior version, and this implementation will likely be improved after additional discussion on transforms kernel dtype/device computation
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| @@ -657,19 +657,22 @@ class Resample(torch.nn.Module): | |||
| Args: | |||
| orig_freq (float, optional): The original frequency of the signal. (Default: ``16000``) | |||
| new_freq (float, optional): The desired frequency. (Default: ``16000``) | |||
| resampling_method (str, optional): The resampling method. (Default: ``'sinc_interpolation'``) | |||
| resampling_method (str, optional): The resampling method. | |||
| Options: [``sinc_interpolation``, ``kaiser_window``] (Default: ``'sinc_interpolation'``) | |||
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followup: This docstring can be improved.
Co-authored-by: Holly Sweeney <77758406+holly1238@users.noreply.github.com>
Add kaiser window as an option for resampling
Jupyter notebook of some results kaiser_resampling__1_.pdf
cc #1487