From 1596f6f414f6f41da66506debb1dff19fffeb3ec Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期一, 24 六月 2024 11:55:17 +0800
Subject: [PATCH] fixbug hotwords
---
runtime/python/websocket/funasr_wss_server.py | 348 +++++++++++++++++++++++++++++++++------------------------
1 files changed, 201 insertions(+), 147 deletions(-)
diff --git a/runtime/python/websocket/funasr_wss_server.py b/runtime/python/websocket/funasr_wss_server.py
index 716e281..1ff5856 100644
--- a/runtime/python/websocket/funasr_wss_server.py
+++ b/runtime/python/websocket/funasr_wss_server.py
@@ -7,137 +7,146 @@
import numpy as np
import argparse
import ssl
-from modelscope.pipelines import pipeline
-from modelscope.utils.constant import Tasks
-from modelscope.utils.logger import get_logger
-tracemalloc.start()
-
-logger = get_logger(log_level=logging.CRITICAL)
-logger.setLevel(logging.CRITICAL)
parser = argparse.ArgumentParser()
-parser.add_argument("--host",
- type=str,
- default="0.0.0.0",
- required=False,
- help="host ip, localhost, 0.0.0.0")
-parser.add_argument("--port",
- type=int,
- default=10095,
- required=False,
- help="grpc server port")
-parser.add_argument("--asr_model",
- type=str,
- default="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
- help="model from modelscope")
-parser.add_argument("--asr_model_online",
- type=str,
- default="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online",
- help="model from modelscope")
-parser.add_argument("--vad_model",
- type=str,
- default="damo/speech_fsmn_vad_zh-cn-16k-common-pytorch",
- help="model from modelscope")
-parser.add_argument("--punc_model",
- type=str,
- default="damo/punc_ct-transformer_zh-cn-common-vad_realtime-vocab272727",
- help="model from modelscope")
-parser.add_argument("--ngpu",
- type=int,
- default=1,
- help="0 for cpu, 1 for gpu")
-parser.add_argument("--ncpu",
- type=int,
- default=4,
- help="cpu cores")
-parser.add_argument("--certfile",
- type=str,
- default="../ssl_key/server.crt",
- required=False,
- help="certfile for ssl")
+parser.add_argument(
+ "--host", type=str, default="0.0.0.0", required=False, help="host ip, localhost, 0.0.0.0"
+)
+parser.add_argument("--port", type=int, default=10095, required=False, help="grpc server port")
+parser.add_argument(
+ "--asr_model",
+ type=str,
+ default="iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
+ help="model from modelscope",
+)
+parser.add_argument("--asr_model_revision", type=str, default="v2.0.4", help="")
+parser.add_argument(
+ "--asr_model_online",
+ type=str,
+ default="iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online",
+ help="model from modelscope",
+)
+parser.add_argument("--asr_model_online_revision", type=str, default="v2.0.4", help="")
+parser.add_argument(
+ "--vad_model",
+ type=str,
+ default="iic/speech_fsmn_vad_zh-cn-16k-common-pytorch",
+ help="model from modelscope",
+)
+parser.add_argument("--vad_model_revision", type=str, default="v2.0.4", help="")
+parser.add_argument(
+ "--punc_model",
+ type=str,
+ default="iic/punc_ct-transformer_zh-cn-common-vad_realtime-vocab272727",
+ help="model from modelscope",
+)
+parser.add_argument("--punc_model_revision", type=str, default="v2.0.4", help="")
+parser.add_argument("--ngpu", type=int, default=1, help="0 for cpu, 1 for gpu")
+parser.add_argument("--device", type=str, default="cuda", help="cuda, cpu")
+parser.add_argument("--ncpu", type=int, default=4, help="cpu cores")
+parser.add_argument(
+ "--certfile",
+ type=str,
+ default="../../ssl_key/server.crt",
+ required=False,
+ help="certfile for ssl",
+)
-parser.add_argument("--keyfile",
- type=str,
- default="../ssl_key/server.key",
- required=False,
- help="keyfile for ssl")
+parser.add_argument(
+ "--keyfile",
+ type=str,
+ default="../../ssl_key/server.key",
+ required=False,
+ help="keyfile for ssl",
+)
args = parser.parse_args()
websocket_users = set()
print("model loading")
+from funasr import AutoModel
+
# asr
-inference_pipeline_asr = pipeline(
- task=Tasks.auto_speech_recognition,
+model_asr = AutoModel(
model=args.asr_model,
+ model_revision=args.asr_model_revision,
ngpu=args.ngpu,
ncpu=args.ncpu,
- model_revision=None)
-
-
+ device=args.device,
+ disable_pbar=True,
+ disable_log=True,
+)
+# asr
+model_asr_streaming = AutoModel(
+ model=args.asr_model_online,
+ model_revision=args.asr_model_online_revision,
+ ngpu=args.ngpu,
+ ncpu=args.ncpu,
+ device=args.device,
+ disable_pbar=True,
+ disable_log=True,
+)
# vad
-inference_pipeline_vad = pipeline(
- task=Tasks.voice_activity_detection,
+model_vad = AutoModel(
model=args.vad_model,
- model_revision=None,
- mode='online',
+ model_revision=args.vad_model_revision,
ngpu=args.ngpu,
ncpu=args.ncpu,
+ device=args.device,
+ disable_pbar=True,
+ disable_log=True,
+ # chunk_size=60,
)
if args.punc_model != "":
- inference_pipeline_punc = pipeline(
- task=Tasks.punctuation,
+ model_punc = AutoModel(
model=args.punc_model,
- model_revision="v1.0.2",
+ model_revision=args.punc_model_revision,
ngpu=args.ngpu,
ncpu=args.ncpu,
+ device=args.device,
+ disable_pbar=True,
+ disable_log=True,
)
else:
- inference_pipeline_punc = None
+ model_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='v1.0.7',
- update_model='v1.0.7',
- 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)
+ print("ws reset now, total num is ", len(websocket_users))
+
+ websocket.status_dict_asr_online["cache"] = {}
+ websocket.status_dict_asr_online["is_final"] = True
+ websocket.status_dict_vad["cache"] = {}
+ websocket.status_dict_vad["is_final"] = True
+ websocket.status_dict_punc["cache"] = {}
+
await websocket.close()
-
-
+
+
async def clear_websocket():
- for websocket in websocket_users:
- await ws_reset(websocket)
- websocket_users.clear()
-
-
-
+ 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()
+ # 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.status_dict_asr = {}
+ websocket.status_dict_asr_online = {"cache": {}, "is_final": False}
+ websocket.status_dict_vad = {"cache": {}, "is_final": False}
+ websocket.status_dict_punc = {"cache": {}}
+ websocket.chunk_interval = 10
websocket.vad_pre_idx = 0
speech_start = False
speech_end_i = -1
@@ -149,43 +158,65 @@
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
+ websocket.status_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"]
+ chunk_size = messagejson["chunk_size"]
+ if isinstance(chunk_size, str):
+ chunk_size = chunk_size.split(",")
+ websocket.status_dict_asr_online["chunk_size"] = [int(x) for x in chunk_size]
if "encoder_chunk_look_back" in messagejson:
- websocket.param_dict_asr_online["encoder_chunk_look_back"] = messagejson["encoder_chunk_look_back"]
+ websocket.status_dict_asr_online["encoder_chunk_look_back"] = messagejson[
+ "encoder_chunk_look_back"
+ ]
if "decoder_chunk_look_back" in messagejson:
- websocket.param_dict_asr_online["decoder_chunk_look_back"] = messagejson["decoder_chunk_look_back"]
+ websocket.status_dict_asr_online["decoder_chunk_look_back"] = messagejson[
+ "decoder_chunk_look_back"
+ ]
+ if "hotword" in messagejson:
+ websocket.status_dict_asr["hotword"] = messagejson["hotwords"]
if "mode" in messagejson:
websocket.mode = messagejson["mode"]
+
+ websocket.status_dict_vad["chunk_size"] = int(
+ websocket.status_dict_asr_online["chunk_size"][1] * 60 / websocket.chunk_interval
+ )
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
+ 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 != -1
- if len(frames_asr_online) % websocket.chunk_interval == 0 or websocket.param_dict_asr_online["is_final"]:
+ websocket.status_dict_asr_online["is_final"] = speech_end_i != -1
+ if (
+ len(frames_asr_online) % websocket.chunk_interval == 0
+ or websocket.status_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)
+ try:
+ await async_asr_online(websocket, audio_in)
+ except:
+ print(f"error in asr streaming, {websocket.status_dict_asr_online}")
frames_asr_online = []
if speech_start:
frames_asr.append(message)
# vad online
- speech_start_i, speech_end_i = await async_vad(websocket, message)
+ try:
+ speech_start_i, speech_end_i = await async_vad(websocket, message)
+ except:
+ print("error in vad")
if speech_start_i != -1:
speech_start = True
- beg_bias = (websocket.vad_pre_idx-speech_start_i)//duration_ms
+ beg_bias = (websocket.vad_pre_idx - speech_start_i) // duration_ms
frames_pre = frames[-beg_bias:]
frames_asr = []
frames_asr.extend(frames_pre)
@@ -194,21 +225,23 @@
# print("vad end point")
if websocket.mode == "2pass" or websocket.mode == "offline":
audio_in = b"".join(frames_asr)
- await async_asr(websocket, audio_in)
+ try:
+ await async_asr(websocket, audio_in)
+ except:
+ print("error in asr offline")
frames_asr = []
speech_start = False
- # frames_asr_online = []
- # websocket.param_dict_asr_online = {"cache": dict()}
+ frames_asr_online = []
+ websocket.status_dict_asr_online["cache"] = {}
if not websocket.is_speaking:
websocket.vad_pre_idx = 0
frames = []
- websocket.param_dict_vad = {'in_cache': dict()}
+ websocket.status_dict_vad["cache"] = {}
else:
frames = frames[-20:]
-
except websockets.ConnectionClosed:
- print("ConnectionClosed...", websocket_users,flush=True)
+ print("ConnectionClosed...", websocket_users, flush=True)
await ws_reset(websocket)
websocket_users.remove(websocket)
except websockets.InvalidState:
@@ -219,62 +252,83 @@
async def async_vad(websocket, audio_in):
- segments_result = inference_pipeline_vad(audio_in=audio_in, param_dict=websocket.param_dict_vad)
+ segments_result = model_vad.generate(input=audio_in, **websocket.status_dict_vad)[0]["value"]
+ # print(segments_result)
speech_start = -1
speech_end = -1
-
- if len(segments_result) == 0 or len(segments_result["text"]) > 1:
+
+ if len(segments_result) == 0 or len(segments_result) > 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 = segments_result["text"][0][1]
+ if segments_result[0][0] != -1:
+ speech_start = segments_result[0][0]
+ if segments_result[0][1] != -1:
+ speech_end = segments_result[0][1]
return speech_start, speech_end
async def async_asr(websocket, audio_in):
- if len(audio_in) > 0:
- # print(len(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:
- mode = "2pass-offline" if "2pass" in websocket.mode else websocket.mode
- message = json.dumps({"mode": mode, "text": rec_result["text"], "wav_name": websocket.wav_name,"is_final":websocket.is_speaking})
- await websocket.send(message)
+ if len(audio_in) > 0:
+ # print(len(audio_in))
+ rec_result = model_asr.generate(input=audio_in, **websocket.status_dict_asr)[0]
+ # print("offline_asr, ", rec_result)
+ if model_punc is not None and len(rec_result["text"]) > 0:
+ # print("offline, before punc", rec_result, "cache", websocket.status_dict_punc)
+ rec_result = model_punc.generate(
+ input=rec_result["text"], **websocket.status_dict_punc
+ )[0]
+ # print("offline, after punc", rec_result)
+ if len(rec_result["text"]) > 0:
+ # print("offline", rec_result)
+ mode = "2pass-offline" if "2pass" in websocket.mode else websocket.mode
+ message = json.dumps(
+ {
+ "mode": mode,
+ "text": rec_result["text"],
+ "wav_name": websocket.wav_name,
+ "is_final": websocket.is_speaking,
+ }
+ )
+ await websocket.send(message)
async def async_asr_online(websocket, audio_in):
if len(audio_in) > 0:
- # 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):
+ # print(websocket.status_dict_asr_online.get("is_final", False))
+ rec_result = model_asr_streaming.generate(
+ input=audio_in, **websocket.status_dict_asr_online
+ )[0]
+ # print("online, ", rec_result)
+ if websocket.mode == "2pass" and websocket.status_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)
- mode = "2pass-online" if "2pass" in websocket.mode else websocket.mode
- message = json.dumps({"mode": mode, "text": rec_result["text"], "wav_name": websocket.wav_name,"is_final":websocket.is_speaking})
- await websocket.send(message)
+ # websocket.status_dict_asr_online["cache"] = dict()
+ if len(rec_result["text"]):
+ mode = "2pass-online" if "2pass" in websocket.mode else websocket.mode
+ message = json.dumps(
+ {
+ "mode": mode,
+ "text": rec_result["text"],
+ "wav_name": websocket.wav_name,
+ "is_final": websocket.is_speaking,
+ }
+ )
+ await websocket.send(message)
-if len(args.certfile)>0:
+
+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)
+ 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)
+ 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()
--
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