54 lines
2.0 KiB
Python
54 lines
2.0 KiB
Python
import argparse
|
|
import os
|
|
import sys
|
|
|
|
from faster_whisper import WhisperModel
|
|
from tqdm import tqdm
|
|
|
|
from tools.stdout_wrapper import SAFE_STDOUT
|
|
|
|
|
|
def transcribe(wav_path, initial_prompt=None):
|
|
segments, _ = model.transcribe(
|
|
wav_path, beam_size=5, language="ja", initial_prompt=initial_prompt
|
|
)
|
|
texts = [segment.text for segment in segments]
|
|
return "".join(texts)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
parser = argparse.ArgumentParser()
|
|
parser.add_argument("--input_dir", type=str, default="raw")
|
|
parser.add_argument("--output_file", type=str, default="esd.list")
|
|
parser.add_argument(
|
|
"--initial_prompt", type=str, default="こんにちは。元気、ですかー？私は……ちゃんと元気だよ！"
|
|
)
|
|
parser.add_argument("--speaker_name", type=str, default=None, required=True)
|
|
parser.add_argument("--model", type=str, default="large-v3")
|
|
|
|
args = parser.parse_args()
|
|
|
|
speaker_name = args.speaker_name
|
|
|
|
input_dir = args.input_dir
|
|
output_file = args.output_file
|
|
initial_prompt = args.initial_prompt
|
|
|
|
model = WhisperModel("large-v3", device="cuda", compute_type="bfloat16")
|
|
|
|
wav_files = [
|
|
os.path.join(input_dir, f) for f in os.listdir(input_dir) if f.endswith(".wav")
|
|
]
|
|
if os.path.exists(output_file):
|
|
print(f"{output_file}が存在するので、バックアップを{output_file}.bakに作成します。")
|
|
if os.path.exists(output_file + ".bak"):
|
|
print(f"{output_file}.bakも存在するので、削除します。")
|
|
os.remove(output_file + ".bak")
|
|
os.rename(output_file, output_file + ".bak")
|
|
|
|
with open(output_file, "w", encoding="utf-8") as f:
|
|
for wav_file in tqdm(wav_files, file=SAFE_STDOUT):
|
|
file_name = os.path.basename(wav_file)
|
|
text = transcribe(wav_file, initial_prompt=initial_prompt)
|
|
f.write(f"{file_name}|{speaker_name}|JP|{text}\n")
|