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Add crossfade between chunks to eliminate noise in concatenation #96

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Add crossfade between chunks to eliminate noise in concatenation #96

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21 changes: 17 additions & 4 deletions dac/model/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -204,8 +204,8 @@ def compress(
range_fn = range if not verbose else tqdm.trange

for i in range_fn(0, nt, hop):
x = audio_signal[..., i : i + n_samples]
x = x.zero_pad(0, max(0, n_samples - x.shape[-1]))
x = audio_signal[..., i : i + n_samples + self.hop_length] # crossfade pad
x = x.zero_pad(0, max(0, n_samples - x.shape[-1] + self.hop_length))

audio_data = x.audio_data.to(self.device)
audio_data = self.preprocess(audio_data, self.sample_rate)
Expand Down Expand Up @@ -271,8 +271,13 @@ def decompress(
r = self.decode(z)
recons.append(r.to(original_device))

recons = torch.cat(recons, dim=-1)
recons = AudioSignal(recons, self.sample_rate)
# recons = torch.cat(recons, dim=-1)
# recons = AudioSignal(recons, self.sample_rate)

chunks = recons[0]
for i in range(1, len(recons)):
chunks = self.crossfade_concat(chunks, recons[i], self.hop_length)
recons = AudioSignal(chunks, self.sample_rate)

resample_fn = recons.resample
loudness_fn = recons.loudness
Expand All @@ -292,3 +297,11 @@ def decompress(

self.padding = original_padding
return recons

@torch.no_grad()
def crossfade_concat(self, chunk1, chunk2, overlap):
fade_out = torch.cos(torch.linspace(0, torch.pi / 2, overlap)) ** 2
fade_in = torch.cos(torch.linspace(torch.pi / 2, 0, overlap)) ** 2
chunk2[..., :overlap] = chunk1[..., -overlap:] * fade_out + chunk2[..., :overlap] * fade_in
chunk = torch.cat((chunk1[..., :-overlap], chunk2), dim=-1)
return chunk