tts接口准备
This commit is contained in:
yanyuxiyangzk@126.com
parent
f5640ef197
commit
1ebd0c90b6
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import asyncio
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import json
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import websockets
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import time
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import logging
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import tracemalloc
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import numpy as np
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import argparse
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import ssl
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parser = argparse.ArgumentParser()
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parser.add_argument("--host",
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type=str,
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default="0.0.0.0",
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required=False,
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help="host ip, localhost, 0.0.0.0")
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parser.add_argument("--port",
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type=int,
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default=10095,
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required=False,
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help="grpc server port")
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parser.add_argument("--asr_model",
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type=str,
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default="iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
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help="model from modelscope")
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parser.add_argument("--asr_model_revision",
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type=str,
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default="v2.0.4",
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help="")
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parser.add_argument("--asr_model_online",
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type=str,
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default="iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online",
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help="model from modelscope")
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parser.add_argument("--asr_model_online_revision",
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type=str,
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default="v2.0.4",
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help="")
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parser.add_argument("--vad_model",
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type=str,
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default="iic/speech_fsmn_vad_zh-cn-16k-common-pytorch",
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help="model from modelscope")
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parser.add_argument("--vad_model_revision",
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type=str,
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default="v2.0.4",
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help="")
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parser.add_argument("--punc_model",
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type=str,
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default="iic/punc_ct-transformer_zh-cn-common-vad_realtime-vocab272727",
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help="model from modelscope")
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parser.add_argument("--punc_model_revision",
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type=str,
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default="v2.0.4",
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help="")
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parser.add_argument("--ngpu",
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type=int,
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default=1,
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help="0 for cpu, 1 for gpu")
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parser.add_argument("--device",
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type=str,
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default="cuda",
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help="cuda, cpu")
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parser.add_argument("--ncpu",
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type=int,
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default=4,
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help="cpu cores")
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parser.add_argument("--certfile",
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type=str,
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default="../../ssl_key/server.crt",
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required=False,
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help="certfile for ssl")
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parser.add_argument("--keyfile",
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type=str,
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default="../../ssl_key/server.key",
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required=False,
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help="keyfile for ssl")
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args = parser.parse_args()
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websocket_users = set()
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print("model loading")
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from funasr import AutoModel
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# asr
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model_asr = AutoModel(model=args.asr_model,
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model_revision=args.asr_model_revision,
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ngpu=args.ngpu,
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ncpu=args.ncpu,
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device=args.device,
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disable_pbar=True,
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disable_log=True,
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)
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# asr
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model_asr_streaming = AutoModel(model=args.asr_model_online,
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model_revision=args.asr_model_online_revision,
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ngpu=args.ngpu,
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ncpu=args.ncpu,
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device=args.device,
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disable_pbar=True,
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disable_log=True,
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)
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# vad
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model_vad = AutoModel(model=args.vad_model,
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model_revision=args.vad_model_revision,
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ngpu=args.ngpu,
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ncpu=args.ncpu,
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device=args.device,
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disable_pbar=True,
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disable_log=True,
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# chunk_size=60,
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)
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if args.punc_model != "":
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model_punc = AutoModel(model=args.punc_model,
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model_revision=args.punc_model_revision,
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ngpu=args.ngpu,
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ncpu=args.ncpu,
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device=args.device,
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disable_pbar=True,
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disable_log=True,
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)
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else:
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model_punc = None
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print("model loaded! only support one client at the same time now!!!!")
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async def ws_reset(websocket):
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print("ws reset now, total num is ",len(websocket_users))
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websocket.status_dict_asr_online["cache"] = {}
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websocket.status_dict_asr_online["is_final"] = True
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websocket.status_dict_vad["cache"] = {}
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websocket.status_dict_vad["is_final"] = True
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websocket.status_dict_punc["cache"] = {}
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await websocket.close()
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async def clear_websocket():
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for websocket in websocket_users:
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await ws_reset(websocket)
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websocket_users.clear()
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async def ws_serve(websocket, path):
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frames = []
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frames_asr = []
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frames_asr_online = []
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global websocket_users
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# await clear_websocket()
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websocket_users.add(websocket)
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websocket.status_dict_asr = {}
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websocket.status_dict_asr_online = {"cache": {}, "is_final": False}
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websocket.status_dict_vad = {'cache': {}, "is_final": False}
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websocket.status_dict_punc = {'cache': {}}
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websocket.chunk_interval = 10
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websocket.vad_pre_idx = 0
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speech_start = False
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speech_end_i = -1
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websocket.wav_name = "microphone"
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websocket.mode = "2pass"
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print("new user connected", flush=True)
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try:
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async for message in websocket:
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if isinstance(message, str):
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messagejson = json.loads(message)
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if "is_speaking" in messagejson:
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websocket.is_speaking = messagejson["is_speaking"]
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websocket.status_dict_asr_online["is_final"] = not websocket.is_speaking
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if "chunk_interval" in messagejson:
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websocket.chunk_interval = messagejson["chunk_interval"]
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if "wav_name" in messagejson:
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websocket.wav_name = messagejson.get("wav_name")
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if "chunk_size" in messagejson:
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chunk_size = messagejson["chunk_size"]
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if isinstance(chunk_size, str):
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chunk_size = chunk_size.split(',')
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websocket.status_dict_asr_online["chunk_size"] = [int(x) for x in chunk_size]
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if "encoder_chunk_look_back" in messagejson:
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websocket.status_dict_asr_online["encoder_chunk_look_back"] = messagejson["encoder_chunk_look_back"]
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if "decoder_chunk_look_back" in messagejson:
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websocket.status_dict_asr_online["decoder_chunk_look_back"] = messagejson["decoder_chunk_look_back"]
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if "hotword" in messagejson:
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websocket.status_dict_asr["hotword"] = messagejson["hotword"]
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if "mode" in messagejson:
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websocket.mode = messagejson["mode"]
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websocket.status_dict_vad["chunk_size"] = int(websocket.status_dict_asr_online["chunk_size"][1]*60/websocket.chunk_interval)
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if len(frames_asr_online) > 0 or len(frames_asr) > 0 or not isinstance(message, str):
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if not isinstance(message, str):
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frames.append(message)
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duration_ms = len(message)//32
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websocket.vad_pre_idx += duration_ms
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# asr online
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frames_asr_online.append(message)
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websocket.status_dict_asr_online["is_final"] = speech_end_i != -1
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if len(frames_asr_online) % websocket.chunk_interval == 0 or websocket.status_dict_asr_online["is_final"]:
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if websocket.mode == "2pass" or websocket.mode == "online":
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audio_in = b"".join(frames_asr_online)
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try:
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await async_asr_online(websocket, audio_in)
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except:
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print(f"error in asr streaming, {websocket.status_dict_asr_online}")
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frames_asr_online = []
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if speech_start:
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frames_asr.append(message)
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# vad online
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try:
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speech_start_i, speech_end_i = await async_vad(websocket, message)
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except:
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print("error in vad")
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if speech_start_i != -1:
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speech_start = True
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beg_bias = (websocket.vad_pre_idx-speech_start_i)//duration_ms
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frames_pre = frames[-beg_bias:]
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frames_asr = []
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frames_asr.extend(frames_pre)
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# asr punc offline
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if speech_end_i != -1 or not websocket.is_speaking:
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# print("vad end point")
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if websocket.mode == "2pass" or websocket.mode == "offline":
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audio_in = b"".join(frames_asr)
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try:
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await async_asr(websocket, audio_in)
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except:
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print("error in asr offline")
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frames_asr = []
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speech_start = False
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frames_asr_online = []
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websocket.status_dict_asr_online["cache"] = {}
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if not websocket.is_speaking:
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websocket.vad_pre_idx = 0
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frames = []
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websocket.status_dict_vad["cache"] = {}
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else:
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frames = frames[-20:]
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except websockets.ConnectionClosed:
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print("ConnectionClosed...", websocket_users,flush=True)
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await ws_reset(websocket)
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websocket_users.remove(websocket)
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except websockets.InvalidState:
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print("InvalidState...")
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except Exception as e:
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print("Exception:", e)
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async def async_vad(websocket, audio_in):
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segments_result = model_vad.generate(input=audio_in, **websocket.status_dict_vad)[0]["value"]
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# print(segments_result)
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speech_start = -1
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speech_end = -1
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if len(segments_result) == 0 or len(segments_result) > 1:
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return speech_start, speech_end
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if segments_result[0][0] != -1:
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speech_start = segments_result[0][0]
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if segments_result[0][1] != -1:
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speech_end = segments_result[0][1]
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return speech_start, speech_end
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async def async_asr(websocket, audio_in):
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if len(audio_in) > 0:
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# print(len(audio_in))
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rec_result = model_asr.generate(input=audio_in, **websocket.status_dict_asr)[0]
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# print("offline_asr, ", rec_result)
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if model_punc is not None and len(rec_result["text"])>0:
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# print("offline, before punc", rec_result, "cache", websocket.status_dict_punc)
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rec_result = model_punc.generate(input=rec_result['text'], **websocket.status_dict_punc)[0]
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# print("offline, after punc", rec_result)
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if len(rec_result["text"])>0:
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# print("offline", rec_result)
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mode = "2pass-offline" if "2pass" in websocket.mode else websocket.mode
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message = json.dumps({"mode": mode, "text": rec_result["text"], "wav_name": websocket.wav_name,"is_final":websocket.is_speaking})
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await websocket.send(message)
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async def async_asr_online(websocket, audio_in):
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if len(audio_in) > 0:
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# print(websocket.status_dict_asr_online.get("is_final", False))
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rec_result = model_asr_streaming.generate(input=audio_in, **websocket.status_dict_asr_online)[0]
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# print("online, ", rec_result)
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if websocket.mode == "2pass" and websocket.status_dict_asr_online.get("is_final", False):
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return
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# websocket.status_dict_asr_online["cache"] = dict()
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if len(rec_result["text"]):
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mode = "2pass-online" if "2pass" in websocket.mode else websocket.mode
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message = json.dumps({"mode": mode, "text": rec_result["text"], "wav_name": websocket.wav_name,"is_final":websocket.is_speaking})
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await websocket.send(message)
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if len(args.certfile)>0:
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ssl_context = ssl.SSLContext(ssl.PROTOCOL_TLS_SERVER)
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# Generate with Lets Encrypt, copied to this location, chown to current user and 400 permissions
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ssl_cert = args.certfile
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ssl_key = args.keyfile
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ssl_context.load_cert_chain(ssl_cert, keyfile=ssl_key)
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start_server = websockets.serve(ws_serve, args.host, args.port, subprotocols=["binary"], ping_interval=None,ssl=ssl_context)
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else:
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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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@ -4,10 +4,21 @@
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python api_v2.py -a 127.0.0.1 -p 9880 -c GPT_SoVITS/configs/tts_infer.yaml
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http://127.0.0.1:9880/set_sovits_weights?weights_path=SoVITS_weights/maimai_e55_s1210.pth
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http://127.0.0.1:9880/set_gpt_weights?weights_path=GPT_weights/maimai-e21.ckpt
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2、接口测试
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http://127.0.0.1:9880/tts?text=我是一个粉刷匠，粉刷本领强。我要把那新房子，刷得更漂亮。刷了房顶又刷墙，刷子像飞一样。哎呀我的小鼻子，变呀变了样。&text_lang=zh&ref_audio_path=mengpai.wav&prompt_lang=zh&prompt_text=呜哇好生气啊！不要把我跟一斗相提并论！&text_split_method=cut5&batch_size=1&media_type=wav&streaming_mode=true
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http://127.0.0.1:9880/set_ava?ava=maimai
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http://127.0.0.1:9880/tts?text=这是一段测试文本，旨在通过多种语言风格和复杂性的内容来全面检验文本到语音系统的性能。接下来，我们会探索各种主题和语言结构，包括文学引用、技术性描述、日常会话以及诗歌等。首先，让我们从一段简单的描述性文本开始：“在一个阳光明媚的下午，一位年轻的旅者站在山顶上，眺望着下方那宽广而繁忙的城市。他的心中充满了对未来的憧憬和对旅途的期待。”这段文本测试了系统对自然景观描写的处理能力和情感表达的细腻程度。&stream=true
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http://127.0.0.1:9880/tts_ava?ava=maimai&text=我是一个粉刷匠，粉刷本领强。我要把那新房子，刷得更漂亮。刷了房顶又刷墙，刷子像飞一样。哎呀我的小鼻子，变呀变了样
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http://127.0.0.1:9880/tts_ava?ava=maimai&text=我是一个粉刷匠，粉刷本领强。我要把那新房子，刷得更漂亮。刷了房顶又刷墙，刷子像飞一样。哎呀我的小鼻子，变呀变了样&streaming_mode=true
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http://127.0.0.1:9880/tts_ava?ava=maimai&text=我是一个粉刷匠，粉刷本领强。我要把那新房子，刷得更漂亮。刷了房顶又刷墙，刷子像飞一样。哎呀我的小鼻子，变呀变了样。&text_lang=zh&ref_audio_path=mengpai.wav&prompt_lang=zh&prompt_text=呜哇好生气啊！不要把我跟一斗相提并论！&text_split_method=cut5&batch_size=1&media_type=wav&streaming_mode=true
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3、使用
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设置角色
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http://127.0.0.1:9880/set_ava?ava=maimai
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tts接口
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http://127.0.0.1:9880/tts_ava?ava=maimai&text=我是一个粉刷匠，粉刷本领强。我要把那新房子，刷得更漂亮。刷了房顶又刷墙，刷子像飞一样。哎呀我的小鼻子，变呀变了样&streaming_mode=true
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