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