import asyncio import json import websockets import time 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.runtime.python.onnxruntime.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") # asr inference_pipeline_asr = pipeline( task=Tasks.auto_speech_recognition, model=args.asr_model, ngpu=args.ngpu, ncpu=args.ncpu, model_revision=None) # vad inference_pipeline_vad = pipeline( task=Tasks.voice_activity_detection, model=args.vad_model, model_revision=None, output_dir=None, batch_size=1, mode='online', ngpu=args.ngpu, ncpu=args.ncpu, ) if args.punc_model != "": inference_pipeline_punc = pipeline( task=Tasks.punctuation, model=args.punc_model, model_revision=None, ngpu=args.ngpu, ncpu=args.ncpu, ) else: inference_pipeline_punc = None inference_pipeline_asr_online = pipeline( task=Tasks.auto_speech_recognition, model=args.asr_model_online, ngpu=args.ngpu, ncpu=args.ncpu, model_revision='v1.0.4') print("model loaded") async def ws_serve(websocket, path): frames = [] frames_asr = [] frames_asr_online = [] global websocket_users websocket_users.add(websocket) websocket.param_dict_asr = {} websocket.param_dict_asr_online = {"cache": dict()} websocket.param_dict_vad = {'in_cache': dict(), "is_final": False} websocket.param_dict_punc = {'cache': list()} websocket.vad_pre_idx = 0 speech_start = False 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') frames.append(audio) duration_ms = len(audio)//32 websocket.vad_pre_idx += duration_ms is_speaking = message["is_speaking"] websocket.param_dict_vad["is_final"] = not is_speaking websocket.param_dict_asr_online["is_final"] = not is_speaking websocket.param_dict_asr_online["chunk_size"] = message["chunk_size"] websocket.wav_name = message.get("wav_name", "demo") # asr online frames_asr_online.append(audio) if len(frames_asr_online) % message["chunk_interval"] == 0: audio_in = b"".join(frames_asr_online) await async_asr_online(websocket, audio_in) frames_asr_online = [] if speech_start: frames_asr.append(audio) # vad online speech_start_i, speech_end_i = await async_vad(websocket, audio) if speech_start_i: speech_start = True beg_bias = (websocket.vad_pre_idx-speech_start_i)//duration_ms frames_pre = frames[-beg_bias:] frames_asr = [] frames_asr.extend(frames_pre) # asr punc offline if speech_end_i or not is_speaking: audio_in = b"".join(frames_asr) await async_asr(websocket, audio_in) frames_asr = [] speech_start = False frames_asr_online = [] websocket.param_dict_asr_online = {"cache": dict()} if not is_speaking: websocket.vad_pre_idx = 0 frames = [] websocket.param_dict_vad = {'in_cache': dict()} else: frames = frames[-20:] except websockets.ConnectionClosed: print("ConnectionClosed...", websocket_users) websocket_users.remove(websocket) except websockets.InvalidState: print("InvalidState...") except Exception as e: print("Exception:", e) async def async_vad(websocket, audio_in): segments_result = inference_pipeline_vad(audio_in=audio_in, param_dict=websocket.param_dict_vad) speech_start = False speech_end = False if len(segments_result) == 0 or len(segments_result["text"]) > 1: return speech_start, speech_end if segments_result["text"][0][0] != -1: speech_start = segments_result["text"][0][0] if segments_result["text"][0][1] != -1: speech_end = True return speech_start, speech_end async def async_asr(websocket, audio_in): if len(audio_in) > 0: # print(len(audio_in)) audio_in = load_bytes(audio_in) rec_result = inference_pipeline_asr(audio_in=audio_in, param_dict=websocket.param_dict_asr) # print(rec_result) if inference_pipeline_punc is not None and 'text' in rec_result and len(rec_result["text"])>0: rec_result = inference_pipeline_punc(text_in=rec_result['text'], param_dict=websocket.param_dict_punc) # print("offline", rec_result) message = json.dumps({"mode": "2pass-offline", "text": rec_result["text"], "wav_name": websocket.wav_name}) await websocket.send(message) async def async_asr_online(websocket, audio_in): if len(audio_in) > 0: 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("online", rec_result) message = json.dumps({"mode": "2pass-online", "text": rec_result["text"], "wav_name": websocket.wav_name}) await websocket.send(message) 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()