GPT-SoVITS/tools/asr/sensevoice.py
XXXXRT666 18af05b5f4 .
2024-07-10 00:04:04 +08:00

72 lines
2.8 KiB
Python

import argparse
import os
import re
import traceback
import torch
from tqdm import tqdm
from funasr import AutoModel
model_dir = "tools/asr/models/SenseVoiceSmall"
model_dir = model_dir if os.path.exists(model_dir) else "iic/SenseVoiceSmall"
def execute_asr(input_folder, output_folder, language, device):
try:
model = AutoModel(model=model_dir,
vad_model="fsmn-vad",
vad_kwargs={"max_single_segment_time": 30000},
)
except:
return print(traceback.format_exc())
input_file_names = os.listdir(input_folder)
input_file_names.sort()
output = []
output_file_name = os.path.basename(input_folder)
if device is None:
device = 'cuda' if torch.cuda.is_available() else 'cpu'
for file_name in tqdm(input_file_names):
try:
file_path = os.path.join(input_folder, file_name)
res = model.generate(
input=file_path,
cache={},
language=language.lower(), # "zn", "en", "yue", "ja", "ko", "nospeech"
use_itn=True,
batch_size_s=0,
device = device
)[0]['text']
text_language = re.search(r'<([^<>]+)>', res).group(1)[1:-1].upper() if language == 'auto' else language.upper()
text = re.sub(r'<[^<>]*>', '', res).replace(' ', '')
output.append(f"{file_path}|{output_file_name}|{text_language}|{text}")
except:
print(traceback.format_exc())
output_folder = output_folder or "output/asr_opt"
os.makedirs(output_folder, exist_ok=True)
output_file_path = os.path.abspath(f'{output_folder}/{output_file_name}.list')
with open(output_file_path, "w", encoding="utf-8") as f:
f.write("\n".join(output))
print(f"ASR 任务完成->标注文件路径: {output_file_path}\n")
return output_file_path
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("-i", "--input_folder", type=str, required=True,
help="Path to the folder containing WAV files.")
parser.add_argument("-o", "--output_folder", type=str, required=True,
help="Output folder to store transcriptions.")
parser.add_argument("-l", "--language", type=str, default='auto',
choices=['auto','zh','en','ja'],
help="Language of the audio files.")
parser.add_argument("-d", "--device", type=str, default=None, choices=['cpu','cuda'],
help="CPU or CUDA")
cmd = parser.parse_args()
output_file_path = execute_asr(
input_folder = cmd.input_folder,
output_folder = cmd.output_folder,
language = cmd.language,
device = cmd.device,
)