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import datetime
from funasr import AutoModel
import streamlit as st
from utils.web_configs import WEB_CONFIGS
from modelscope import snapshot_download
from modelscope.utils.constant import Invoke, ThirdParty
from funasr.download.name_maps_from_hub import name_maps_ms as NAME_MAPS_MS
@st.cache_resource
def load_asr_model():
# 模型下载
model_path_info = dict()
for model_name in ["paraformer-zh", "fsmn-vad", "ct-punc"]:
print(f"downloading asr model : {NAME_MAPS_MS[model_name]}")
mode_dir = snapshot_download(
NAME_MAPS_MS[model_name],
revision="master",
user_agent={Invoke.KEY: Invoke.PIPELINE, ThirdParty.KEY: "funasr"},
cache_dir=WEB_CONFIGS.ASR_MODEL_DIR,
)
model_path_info[model_name] = mode_dir
NAME_MAPS_MS[model_name] = mode_dir # 更新
print(f"ASR model path info = {model_path_info}")
# paraformer-zh is a multi-functional asr model
# use vad, punc, spk or not as you need
model = AutoModel(
model="paraformer-zh", # 语音识别，带时间戳输出，非实时
vad_model="fsmn-vad", # 语音端点检测，实时
punc_model="ct-punc", # 标点恢复
# spk_model="cam++" # 说话人确认/分割
model_path=model_path_info["paraformer-zh"],
vad_kwargs={"model_path": model_path_info["fsmn-vad"]},
punc_kwargs={"model_path": model_path_info["ct-punc"]},
)
return model
def process_asr(model: AutoModel, wav_path):
# https://github.com/modelscope/FunASR/blob/main/README_zh.md#%E5%AE%9E%E6%97%B6%E8%AF%AD%E9%9F%B3%E8%AF%86%E5%88%AB
f_start_time = datetime.datetime.now()
res = model.generate(input=wav_path, batch_size_s=50, hotword="魔搭")
delta_time = datetime.datetime.now() - f_start_time
try:
print(f"ASR using time {delta_time}s, text: ", res[0]["text"])
res_str = res[0]["text"]
except Exception as e:
print("ASR 解析失败，无法获取到文字")
return ""
return res_str
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