Matching the STFT of paderbox and torch

stft_torch_paderbox.py

import torch
import paderbox
import numpy as np
from scipy.signal import hamming, blackman, get_window, hann
import matplotlib.pyplot as plt


f = 1500.0  # exactly periodic
fs = 48000.0
nfft = 512
hop = 128

demo = np.sin(2 * np.pi * f / fs * np.arange(fs))

# To make the comparison easier, we pad the input signal to
# make it a multiple of the FFT size
pad_size = nfft - hop
padding = np.zeros(pad_size)
demo = np.concatenate([demo, np.zeros(pad_size)])

# torch
# - use `center=False`
# - zero-pad the front of the signal
demo_lr = np.concatenate([padding, demo])
demo_lr = torch.from_numpy(demo_lr)
win_pt = torch.hamming_window(nfft, dtype=demo_lr.dtype)
PT = torch.stft(
    demo_lr,
    n_fft=nfft,
    hop_length=hop,
    window=win_pt,
    return_complex=True,
    pad_mode="constant",
    center=False,
)
recon_pt = torch.istft(PT, n_fft=nfft, hop_length=hop, window=win_pt, center=False)
recon_pt = recon_pt[pad_size:]
recon_pt = recon_pt.numpy()
PT = PT.numpy()
print("torch: reconstruction exact ?", np.allclose(recon_pt, demo))

# paderbox
AR = paderbox.transform.stft(
    demo_lr,
    size=nfft,
    shift=hop,
    fading=False,
    window=hamming,
    # window=hamming_win,
    # symmetric_window=True,
)
recon_ar = paderbox.transform.istft(
    AR, size=nfft, shift=hop, fading=False, window=hamming
)
AR = AR.T
recon_ar = recon_ar[pad_size:]
print(
    "pader: reconstruction exact ?",
    np.allclose(recon_ar, demo),
)

print("difference between librosa's and pra's STFT", abs(PT - AR).max())

I usually use a Hamming window for separation...

…

On Sat, Dec 24, 2022, 18:58 Desh Raj ***@***.***> wrote: ***@***.**** commented on this gist. ------------------------------ I also reported the same issue! pytorch/pytorch#91309 <pytorch/pytorch#91309> Does it have to be Blackman ? You can also use center=True, which has slightly different padding, but should not change quality. I will try out other options and see how they compare in terms of downstream WER. — Reply to this email directly, view it on GitHub <https://gist.github.com/d395f5aa5e5c5fa07c7cbcf51d543413#gistcomment-4412594> or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAIQ7NILBT55KZAXM663HEDWO3CL3BFKMF2HI4TJMJ2XIZLTSKBKK5TBNR2WLJDHNFZXJJDOMFWWLK3UNBZGKYLEL52HS4DFQKSXMYLMOVS2I5DSOVS2I3TBNVS3W5DIOJSWCZC7OBQXE5DJMNUXAYLOORPWCY3UNF3GS5DZVRZXKYTKMVRXIX3UPFYGLK2HNFZXIQ3PNVWWK3TUUZ2G64DJMNZZDAVEOR4XAZNEM5UXG5FFOZQWY5LFVEYTCOJZGU3TANZRU52HE2LHM5SXFJTDOJSWC5DF> . You are receiving this email because you authored the thread. Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub> .