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import os |
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import json |
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import librosa |
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from tqdm import tqdm |
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from glob import glob |
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from collections import defaultdict |
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from utils.util import has_existed |
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def get_lines(file): |
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with open(file, "r") as f: |
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lines = f.readlines() |
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lines = [l.strip() for l in lines] |
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return lines |
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def vctk_statistics(data_dir): |
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speakers = [] |
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speakers2utts = defaultdict(list) |
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speaker_infos = glob(data_dir + "/wav48_silence_trimmed" + "/*") |
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for speaker_info in speaker_infos: |
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speaker = speaker_info.split("/")[-1] |
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if speaker == "log.txt": |
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continue |
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speakers.append(speaker) |
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utts = glob(speaker_info + "/*") |
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for utt in utts: |
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uid = ( |
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utt.split("/")[-1].split("_")[1] |
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+ "_" |
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+ utt.split("/")[-1].split("_")[2].split(".")[0] |
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) |
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speakers2utts[speaker].append(uid) |
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unique_speakers = list(set(speakers)) |
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unique_speakers.sort() |
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print("Speakers: \n{}".format("\t".join(unique_speakers))) |
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return speakers2utts, unique_speakers |
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def vctk_speaker_infos(data_dir): |
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file = os.path.join(data_dir, "speaker-info.txt") |
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lines = get_lines(file) |
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ID2speakers = defaultdict() |
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for l in tqdm(lines): |
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items = l.replace(" ", "") |
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if items[:2] == "ID": |
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continue |
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if items[0] == "p": |
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id = items[:4] |
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gender = items[6] |
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elif items[0] == "s": |
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id = items[:2] |
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gender = items[4] |
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if gender == "F": |
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speaker = "female_{}".format(id) |
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elif gender == "M": |
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speaker = "male_{}".format(id) |
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ID2speakers[id] = speaker |
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return ID2speakers |
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def main(output_path, dataset_path, TEST_NUM_OF_EVERY_SPEAKER=3): |
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print("-" * 10) |
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print("Preparing test samples for vctk...") |
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save_dir = os.path.join(output_path, "vctk") |
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os.makedirs(save_dir, exist_ok=True) |
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train_output_file = os.path.join(save_dir, "train.json") |
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test_output_file = os.path.join(save_dir, "test.json") |
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singer_dict_file = os.path.join(save_dir, "singers.json") |
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utt2singer_file = os.path.join(save_dir, "utt2singer") |
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if has_existed(train_output_file): |
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return |
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utt2singer = open(utt2singer_file, "w") |
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vctk_dir = dataset_path |
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ID2speakers = vctk_speaker_infos(vctk_dir) |
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speaker2utts, unique_speakers = vctk_statistics(vctk_dir) |
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train = [] |
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test = [] |
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train_index_count = 0 |
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test_index_count = 0 |
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test_speaker_count = defaultdict(int) |
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train_total_duration = 0 |
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test_total_duration = 0 |
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for i, speaker in enumerate(speaker2utts.keys()): |
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for chosen_uid in tqdm( |
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speaker2utts[speaker], |
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desc="Speaker {}/{}, #Train = {}, #Test = {}".format( |
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i + 1, len(speaker2utts), train_index_count, test_index_count |
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), |
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): |
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res = { |
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"Dataset": "vctk", |
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"Singer": ID2speakers[speaker], |
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"Uid": "{}#{}".format(ID2speakers[speaker], chosen_uid), |
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} |
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res["Path"] = "{}/{}_{}.flac".format(speaker, speaker, chosen_uid) |
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res["Path"] = os.path.join(vctk_dir, "wav48_silence_trimmed", res["Path"]) |
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assert os.path.exists(res["Path"]) |
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duration = librosa.get_duration(filename=res["Path"]) |
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res["Duration"] = duration |
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if test_speaker_count[speaker] < TEST_NUM_OF_EVERY_SPEAKER: |
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res["index"] = test_index_count |
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test_total_duration += duration |
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test.append(res) |
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test_index_count += 1 |
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test_speaker_count[speaker] += 1 |
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else: |
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res["index"] = train_index_count |
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train_total_duration += duration |
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train.append(res) |
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train_index_count += 1 |
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utt2singer.write("{}\t{}\n".format(res["Uid"], res["Singer"])) |
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print("#Train = {}, #Test = {}".format(len(train), len(test))) |
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print( |
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"#Train hours= {}, #Test hours= {}".format( |
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train_total_duration / 3600, test_total_duration / 3600 |
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) |
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) |
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with open(train_output_file, "w") as f: |
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json.dump(train, f, indent=4, ensure_ascii=False) |
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with open(test_output_file, "w") as f: |
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json.dump(test, f, indent=4, ensure_ascii=False) |
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singer_lut = {name: i for i, name in enumerate(unique_speakers)} |
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with open(singer_dict_file, "w") as f: |
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json.dump(singer_lut, f, indent=4, ensure_ascii=False) |
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