Comparison of audio resampling libraries. View the notebook: https://nbviewer.jupyter.org/github/jonashaag/audio-resampling-in-python/blob/master/Audio%20Resampling%20in%20Python.ipynb
- Good:
scikit.samplerate/scikits-samplerate/samplerate/libsampleratelibrosa/resampy("kaiser_best")julius
- Acceptable:
nnresamplelilfiltertorchaudio(transforms.Resample+resample_waveform)librosa/resampy("kaiser_fast")
- Bad:
scipy.signal.resample
Downsampling from 48 kHz to 44.1 kHz.
| Library | Time on CPU | Time on GPU |
|---|---|---|
soxr |
1.16 ms | no support |
scipy.signal.resample |
2.42 ms | no support |
lilfilter |
4.23 ms | ? |
torchaudio (transforms.Resample) |
9.98 ms | ? |
torchaudio (resample_waveform) |
10 ms | ? |
resampy ("kaiser_fast") |
10.5 ms | no support |
nnresample |
16 ms | no support |
julius |
16.2 ms | ? |
resampy ("kaiser_best") |
44.8 ms | no support |
scikits.samplerate |
75.5 ms | no support |
samplerate |
76.8 ms | no support |