import asyncio
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import json
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import websockets
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import time
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from queue import Queue
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import threading
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import logging
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import tracemalloc
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import numpy as np
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from parse_args import args
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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from modelscope.utils.logger import get_logger
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from funasr_onnx.utils.frontend import load_bytes
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tracemalloc.start()
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logger = get_logger(log_level=logging.CRITICAL)
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logger.setLevel(logging.CRITICAL)
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websocket_users = set()
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print("model loading")
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inference_pipeline_asr_online = pipeline(
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task=Tasks.auto_speech_recognition,
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model=args.asr_model_online,
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model_revision='v1.0.4')
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print("model loaded")
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async def ws_serve(websocket, path):
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frames_online = []
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global websocket_users
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websocket.send_msg = Queue()
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websocket_users.add(websocket)
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websocket.param_dict_asr_online = {"cache": dict()}
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websocket.speek_online = Queue()
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ss_online = threading.Thread(target=asr_online, args=(websocket,))
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ss_online.start()
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try:
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async for message in websocket:
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message = json.loads(message)
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is_finished = message["is_finished"]
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if not is_finished:
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audio = bytes(message['audio'], 'ISO-8859-1')
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is_speaking = message["is_speaking"]
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websocket.param_dict_asr_online["is_final"] = not is_speaking
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websocket.param_dict_asr_online["chunk_size"] = message["chunk_size"]
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frames_online.append(audio)
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if len(frames_online) % message["chunk_interval"] == 0 or not is_speaking:
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audio_in = b"".join(frames_online)
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websocket.speek_online.put(audio_in)
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frames_online = []
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if not websocket.send_msg.empty():
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await websocket.send(websocket.send_msg.get())
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websocket.send_msg.task_done()
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except websockets.ConnectionClosed:
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print("ConnectionClosed...", websocket_users) # 链接断开
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websocket_users.remove(websocket)
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except websockets.InvalidState:
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print("InvalidState...") # 无效状态
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except Exception as e:
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print("Exception:", e)
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def asr_online(websocket): # ASR推理
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global websocket_users
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while websocket in websocket_users:
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if not websocket.speek_online.empty():
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audio_in = websocket.speek_online.get()
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websocket.speek_online.task_done()
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if len(audio_in) > 0:
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# print(len(audio_in))
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audio_in = load_bytes(audio_in)
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rec_result = inference_pipeline_asr_online(audio_in=audio_in,
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param_dict=websocket.param_dict_asr_online)
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if websocket.param_dict_asr_online["is_final"]:
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websocket.param_dict_asr_online["cache"] = dict()
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if "text" in rec_result:
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if rec_result["text"] != "sil" and rec_result["text"] != "waiting_for_more_voice":
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print(rec_result["text"])
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message = json.dumps({"mode": "online", "text": rec_result["text"]})
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websocket.send_msg.put(message)
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time.sleep(0.005)
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start_server = websockets.serve(ws_serve, args.host, args.port, subprotocols=["binary"], ping_interval=None)
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asyncio.get_event_loop().run_until_complete(start_server)
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asyncio.get_event_loop().run_forever()
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