FunASR/funasr/runtime/python/websocket/wss_srv_asr.py
zhaomingwork 6f3b508485
For python ws online asr slow problem (#582)
* for python online ws srv become slow problem

* little change for message
2023-06-02 13:02:29 +08:00

233 lines
9.0 KiB
Python

import asyncio
import json
import websockets
import time
import logging
import tracemalloc
import numpy as np
import ssl
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="v1.0.2",
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',
update_model='v1.0.4'
mode='paraformer_streaming')
print("model loaded! only support one client at the same time now!!!!")
async def ws_reset(websocket):
print("ws reset now, total num is ",len(websocket_users))
websocket.param_dict_asr_online = {"cache": dict()}
websocket.param_dict_vad = {'in_cache': dict(), "is_final": True}
websocket.param_dict_asr_online["is_final"]=True
audio_in=b''.join(np.zeros(int(16000),dtype=np.int16))
inference_pipeline_vad(audio_in=audio_in, param_dict=websocket.param_dict_vad)
inference_pipeline_asr_online(audio_in=audio_in, param_dict=websocket.param_dict_asr_online)
await websocket.close()
async def clear_websocket():
for websocket in websocket_users:
await ws_reset(websocket)
websocket_users.clear()
async def ws_serve(websocket, path):
frames = []
frames_asr = []
frames_asr_online = []
global websocket_users
await clear_websocket()
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
speech_end_i = False
websocket.wav_name = "microphone"
websocket.mode = "2pass"
print("new user connected", flush=True)
try:
async for message in websocket:
if isinstance(message, str):
messagejson = json.loads(message)
if "is_speaking" in messagejson:
websocket.is_speaking = messagejson["is_speaking"]
websocket.param_dict_asr_online["is_final"] = not websocket.is_speaking
if "chunk_interval" in messagejson:
websocket.chunk_interval = messagejson["chunk_interval"]
if "wav_name" in messagejson:
websocket.wav_name = messagejson.get("wav_name")
if "chunk_size" in messagejson:
websocket.param_dict_asr_online["chunk_size"] = messagejson["chunk_size"]
if "mode" in messagejson:
websocket.mode = messagejson["mode"]
if len(frames_asr_online) > 0 or len(frames_asr) > 0 or not isinstance(message, str):
if not isinstance(message, str):
frames.append(message)
duration_ms = len(message)//32
websocket.vad_pre_idx += duration_ms
# asr online
frames_asr_online.append(message)
websocket.param_dict_asr_online["is_final"] = speech_end_i
if len(frames_asr_online) % websocket.chunk_interval == 0 or websocket.param_dict_asr_online["is_final"]:
if websocket.mode == "2pass" or websocket.mode == "online":
audio_in = b"".join(frames_asr_online)
await async_asr_online(websocket, audio_in)
frames_asr_online = []
if speech_start:
frames_asr.append(message)
# vad online
speech_start_i, speech_end_i = await async_vad(websocket, message)
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 websocket.is_speaking:
# print("vad end point")
if websocket.mode == "2pass" or websocket.mode == "offline":
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 websocket.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,flush=True)
await ws_reset(websocket)
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)
if 'text' in 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)
# print(websocket.param_dict_asr_online.get("is_final", False))
rec_result = inference_pipeline_asr_online(audio_in=audio_in,
param_dict=websocket.param_dict_asr_online)
# print(rec_result)
if websocket.mode == "2pass" and websocket.param_dict_asr_online.get("is_final", False):
return
# 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)
if len(args.certfile)>0:
ssl_context = ssl.SSLContext(ssl.PROTOCOL_TLS_SERVER)
# Generate with Lets Encrypt, copied to this location, chown to current user and 400 permissions
ssl_cert = args.certfile
ssl_key = args.keyfile
ssl_context.load_cert_chain(ssl_cert, keyfile=ssl_key)
start_server = websockets.serve(ws_serve, args.host, args.port, subprotocols=["binary"], ping_interval=None,ssl=ssl_context)
else:
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()