Utilities for filtering and resampling signals
Utilities for resampling and filtering audio data
This repository exports a Python package
lilfilter containing certain
utilities for filtering and resampling audio data.
One quite-useful thing is class Resampler:
python3 >>> import lilfilter >>> # ... let a be a Torch tensor of size (num_channels, num_samples) >>> # that we want to downsample from 42.1kHz to 16kHz. Note, >>> # the sampling rates must be integers; only their ratio >>> # matters. >>> r = lilfilter.Resampler(42100, 16000, dtype=torch.float32) >>> b = r.resample(a)
Another thing that's useful is class Multistreamer, which can turn a signal into multiple parallel signals at a lower sampling rate, where pairs of those signals represent the (real,complex) part of one complex frequency band of the input.
>>> import lilfilter >>> num_freq_bands = 8 >>> m = lilfilter.Multistreamer(num_freq_bands) >>> >>> # ... let a be a Torch tensor of size (num_channels, num_samples) >>> # that we want to `demultiplex`. >>> >>> b = m.split(a) >>> # now b is of size (num_channels, 2, num_freq_bands, num_samples/num_freq_bands) >>> # (note: the dim of the last axis may be slightly different from that number). >>> # You can in principle manipulate b somehow, e.g. do some kind of machine >>> # learning with it, and then reconstruct to the original format: >>> >>> c = m.merge(b) >>> # now c is of size (num_channels, 8*(num_samples/8)) and will be extremely >>> # close to a.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size lilfilter-0.0.1.tar.gz (69.2 kB)||File type Source||Python version None||Upload date||Hashes View|