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@ -59,9 +59,10 @@ def prepare_vox(
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# )
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# )
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manifests = {}
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manifests = {}
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subset = spk_id.split('_')[0]
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spk_idx = spk_id.split('_')[1]
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#dataset_parts = ["train", "dev", "test"]
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#dataset_parts = ["train", "dev", "test"]
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dataset_parts = [spk_id]
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dataset_parts = [spk_idx]
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if output_dir is not None:
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if output_dir is not None:
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output_dir = Path(output_dir)
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output_dir = Path(output_dir)
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output_dir.mkdir(parents=True, exist_ok=True)
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output_dir.mkdir(parents=True, exist_ok=True)
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@ -81,7 +82,8 @@ def prepare_vox(
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#part_file_names = list(map(lambda x: x.strip('.wav'), os.listdir(part_path)))
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#part_file_names = list(map(lambda x: x.strip('.wav'), os.listdir(part_path)))
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part_file_names = sorted(glob.glob(str(part_path)+'/*.wav'))
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part_file_names = sorted(glob.glob(str(part_path)+'/*.wav'))
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part_file_names = [name.split('/')[-1].replace('.wav', '') for name in part_file_names]
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part_file_names = [name.split('/')[-1].replace('.wav', '') for name in part_file_names]
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txt_path = os.path.join(corpus_dir, f"../{spk_id}/texts")
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txt_path = os.path.join(corpus_dir, f"../{spk_idx}_texts")
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print(txt_path)
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futures = []
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futures = []
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for trans_path in tqdm(
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for trans_path in tqdm(
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