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Fix issues
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9d67b757f0
commit
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@ -68,20 +68,12 @@ def mel_spectrogram(
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if torch.max(y) > 1.:
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print('max value is ', torch.max(y))
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# global mel_basis, hann_window
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# if fmax not in mel_basis:
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# mel = librosa_mel_fn(sampling_rate, n_fft, num_mels, fmin, fmax)
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# mel_basis[str(fmax)+'_'+str(y.device)] = torch.from_numpy(mel).float().to(y.device)
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# hann_window[str(y.device)] = torch.hann_window(win_size).to(y.device)
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global mel_basis, hann_window
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dtype_device = str(y.dtype) + '_' + str(y.device)
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fmax_dtype_device = str(fmax) + '_' + dtype_device
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wnsize_dtype_device = str(win_size) + '_' + dtype_device
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if fmax_dtype_device not in mel_basis:
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if fmax not in mel_basis:
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mel = librosa_mel_fn(sampling_rate, n_fft, num_mels, fmin, fmax)
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mel_basis[fmax_dtype_device] = torch.from_numpy(mel).to(dtype=y.dtype, device=y.device)
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if wnsize_dtype_device not in hann_window:
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hann_window[wnsize_dtype_device] = torch.hann_window(win_size).to(dtype=y.dtype, device=y.device)
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mel_basis[str(fmax)+'_'+str(y.device)] = torch.from_numpy(mel).float().to(y.device)
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hann_window[str(y.device)] = torch.hann_window(win_size).to(y.device)
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y = torch.nn.functional.pad(y.unsqueeze(1), (int((n_fft-hop_size)/2), int((n_fft-hop_size)/2)), mode='reflect')
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y = y.squeeze(1)
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38
vits.ipynb
vendored
38
vits.ipynb
vendored
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@ -377,6 +377,44 @@
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" metadata_file.write(new_info)\n",
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"metadata_file.close()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"from pathlib import Path\n",
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"import os\n",
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"import shutil\n",
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"emo_root = Path('../audiodata/SV2TTS/synthesizer').joinpath('emo')\n",
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"# raw_root = Path('../audiodata/aidatatang_200zh/corpus/train')\n",
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"# emo_file_list = emo_root.glob(\"**/*.npy\")\n",
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"# for emo_file in emo_file_list:\n",
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"# if emo_file.name.endswith('wav__00.npy'):\n",
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"# folder = emo_file.parent\n",
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"# os.rename(emo_file, folder.joinpath(emo_file.name.replace(\"__00\", \"_00\")))\n",
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" # shutil.move(emo_file, emo_root.joinpath(emo_file.name))\n",
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"\n",
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"root = Path('../audiodata/SV2TTS/synthesizer')\n",
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"dict_info = []\n",
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"with open(root.joinpath(\"train.txt\"), \"r\", encoding=\"utf-8\") as dict_meta:\n",
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" for raw in dict_meta:\n",
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" if not raw:\n",
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" continue\n",
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" v = raw.split(\"|\")[0].replace(\"audio\",\"emo\")\n",
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" emo_fpath = root.joinpath(\"emo\").joinpath(v)\n",
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" if emo_fpath.exists():\n",
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" dict_info.append(raw)\n",
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" # else:\n",
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" # print(emo_fpath)\n",
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"# Iterate over each wav\n",
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"meta2 = Path('../audiodata/SV2TTS/synthesizer/train2.txt')\n",
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"metadata_file = meta2.open(\"w\", encoding=\"utf-8\")\n",
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"for new_info in dict_info:\n",
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" metadata_file.write(new_info)\n",
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"metadata_file.close()"
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]
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}
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],
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"metadata": {
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