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