168 lines
6.1 KiB
Python
168 lines
6.1 KiB
Python
import json
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import os
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from collections import defaultdict
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from random import shuffle
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from typing import Optional
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import click
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from tqdm import tqdm
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from config import config
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from text.cleaner import clean_text
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from common.stdout_wrapper import SAFE_STDOUT
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from common.log import logger
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preprocess_text_config = config.preprocess_text_config
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# Count lines for tqdm
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def count_lines(file_path: str):
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with open(file_path, "r", encoding="utf-8") as file:
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return sum(1 for _ in file)
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@click.command()
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@click.option(
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"--transcription-path",
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default=preprocess_text_config.transcription_path,
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type=click.Path(exists=True, file_okay=True, dir_okay=False),
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)
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@click.option("--cleaned-path", default=preprocess_text_config.cleaned_path)
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@click.option("--train-path", default=preprocess_text_config.train_path)
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@click.option("--val-path", default=preprocess_text_config.val_path)
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@click.option(
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"--config-path",
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default=preprocess_text_config.config_path,
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type=click.Path(exists=True, file_okay=True, dir_okay=False),
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)
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@click.option("--val-per-lang", default=preprocess_text_config.val_per_lang)
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@click.option("--max-val-total", default=preprocess_text_config.max_val_total)
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@click.option("--clean/--no-clean", default=preprocess_text_config.clean)
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@click.option("-y", "--yml_config")
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@click.option("--use_jp_extra", is_flag=True)
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def preprocess(
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transcription_path: str,
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cleaned_path: Optional[str],
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train_path: str,
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val_path: str,
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config_path: str,
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val_per_lang: int,
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max_val_total: int,
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clean: bool,
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yml_config: str, # 这个不要删
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use_jp_extra: bool,
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):
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if cleaned_path == "" or cleaned_path is None:
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cleaned_path = transcription_path + ".cleaned"
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error_log_path = os.path.join(os.path.dirname(cleaned_path), "text_error.log")
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error_count = 0
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if clean:
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total_lines = count_lines(transcription_path)
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with open(cleaned_path, "w", encoding="utf-8") as out_file:
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with open(transcription_path, "r", encoding="utf-8") as trans_file:
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for line in tqdm(trans_file, file=SAFE_STDOUT, total=total_lines):
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try:
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utt, spk, language, text = line.strip().split("|")
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norm_text, phones, tones, word2ph = clean_text(
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text, language, use_jp_extra
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)
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out_file.write(
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"{}|{}|{}|{}|{}|{}|{}\n".format(
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utt,
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spk,
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language,
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norm_text,
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" ".join(phones),
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" ".join([str(i) for i in tones]),
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" ".join([str(i) for i in word2ph]),
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)
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)
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except Exception as e:
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logger.error(f"An error occurred at line:\n{line.strip()}\n{e}")
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with open(error_log_path, "a", encoding="utf-8") as error_log:
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error_log.write(f"{line.strip()}\n{e}\n\n")
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error_count += 1
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transcription_path = cleaned_path
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spk_utt_map = defaultdict(list)
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spk_id_map = {}
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current_sid = 0
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with open(transcription_path, "r", encoding="utf-8") as f:
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audioPaths = set()
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countSame = 0
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countNotFound = 0
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for line in f.readlines():
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utt, spk, language, text, phones, tones, word2ph = line.strip().split("|")
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if utt in audioPaths:
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# 过滤数据集错误：相同的音频匹配多个文本，导致后续bert出问题
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logger.warning(f"Same audio matches multiple texts: {line}")
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countSame += 1
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continue
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if not os.path.isfile(utt):
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# 过滤数据集错误：不存在对应音频
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logger.warning(f"Audio not found: {utt}")
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countNotFound += 1
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continue
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audioPaths.add(utt)
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spk_utt_map[language].append(line)
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if spk not in spk_id_map.keys():
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spk_id_map[spk] = current_sid
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current_sid += 1
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if countSame > 0 or countNotFound > 0:
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logger.warning(
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f"Total repeated audios: {countSame}, Total number of audio not found: {countNotFound}"
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)
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train_list = []
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val_list = []
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for spk, utts in spk_utt_map.items():
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shuffle(utts)
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val_list += utts[:val_per_lang]
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train_list += utts[val_per_lang:]
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shuffle(val_list)
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if len(val_list) > max_val_total:
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train_list += val_list[max_val_total:]
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val_list = val_list[:max_val_total]
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with open(train_path, "w", encoding="utf-8") as f:
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for line in train_list:
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f.write(line)
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with open(val_path, "w", encoding="utf-8") as f:
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for line in val_list:
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f.write(line)
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json_config = json.load(open(config_path, encoding="utf-8"))
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json_config["data"]["spk2id"] = spk_id_map
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json_config["data"]["n_speakers"] = len(spk_id_map)
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# 新增写入：写入训练版本、数据集路径
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# json_config["version"] = latest_version
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json_config["data"]["training_files"] = os.path.normpath(train_path).replace(
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"\\", "/"
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)
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json_config["data"]["validation_files"] = os.path.normpath(val_path).replace(
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"\\", "/"
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)
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with open(config_path, "w", encoding="utf-8") as f:
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json.dump(json_config, f, indent=2, ensure_ascii=False)
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if error_count > 0:
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logger.error(
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f"An error occurred in {error_count} lines. Please check {error_log_path} for details. You can proceed with lines that do not have errors."
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)
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raise Exception(
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f"An error occurred in {error_count} lines. Please check {error_log_path} for details. You can proceed with lines that do not have errors."
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)
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else:
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logger.info(
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"Training set and validation set generation from texts is complete!"
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)
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if __name__ == "__main__":
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preprocess()
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