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| | | import aiofiles |
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| | | import ffmpeg |
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| | | import uvicorn |
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| | | from fastapi import FastAPI, File, UploadFile, Body |
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| | | from modelscope.pipelines import pipeline |
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| | | from modelscope.utils.constant import Tasks |
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| | | from fastapi import FastAPI, File, UploadFile |
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| | | from modelscope.utils.logger import get_logger |
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| | | |
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| | | logger = get_logger(log_level=logging.CRITICAL) |
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| | | logger.setLevel(logging.CRITICAL) |
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| | | from funasr import AutoModel |
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| | | |
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| | | logger = get_logger(log_level=logging.INFO) |
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| | | logger.setLevel(logging.INFO) |
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| | | |
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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=8000, |
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| | | required=False, |
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| | | help="server port") |
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| | | parser.add_argument("--asr_model", |
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| | | type=str, |
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| | | default="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch", |
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| | | help="offline asr model from modelscope") |
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| | | parser.add_argument("--vad_model", |
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| | | type=str, |
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| | | default="damo/speech_fsmn_vad_zh-cn-16k-common-pytorch", |
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| | | help="vad model from modelscope") |
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| | | parser.add_argument("--punc_model", |
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| | | type=str, |
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| | | default="damo/punc_ct-transformer_cn-en-common-vocab471067-large", |
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| | | help="punc model from modelscope") |
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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("--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("--hotword_path", |
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| | | type=str, |
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| | | default=None, |
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| | | help="hot word txt path, only the hot word model works") |
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| | | parser.add_argument("--certfile", |
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| | | type=str, |
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| | | default=None, |
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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=None, |
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| | | required=False, |
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| | | help="keyfile for ssl") |
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| | | parser.add_argument("--temp_dir", |
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| | | type=str, |
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| | | default="temp_dir/", |
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| | | required=False, |
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| | | help="temp dir") |
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| | | parser.add_argument( |
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| | | "--host", type=str, default="0.0.0.0", required=False, help="host ip, localhost, 0.0.0.0" |
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| | | ) |
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| | | parser.add_argument("--port", type=int, default=8000, required=False, help="server port") |
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| | | parser.add_argument( |
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| | | "--asr_model", |
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| | | type=str, |
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| | | default="paraformer-zh", |
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| | | help="asr model from https://github.com/alibaba-damo-academy/FunASR?tab=readme-ov-file#model-zoo", |
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| | | ) |
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| | | parser.add_argument("--asr_model_revision", type=str, default="v2.0.4", help="") |
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| | | parser.add_argument( |
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| | | "--vad_model", |
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| | | type=str, |
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| | | default="fsmn-vad", |
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| | | help="vad model from https://github.com/alibaba-damo-academy/FunASR?tab=readme-ov-file#model-zoo", |
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| | | ) |
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| | | parser.add_argument("--vad_model_revision", type=str, default="v2.0.4", help="") |
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| | | parser.add_argument( |
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| | | "--punc_model", |
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| | | type=str, |
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| | | default="ct-punc-c", |
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| | | help="model from https://github.com/alibaba-damo-academy/FunASR?tab=readme-ov-file#model-zoo", |
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| | | ) |
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| | | parser.add_argument("--punc_model_revision", type=str, default="v2.0.4", help="") |
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| | | parser.add_argument("--ngpu", type=int, default=1, help="0 for cpu, 1 for gpu") |
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| | | parser.add_argument("--device", type=str, default="cuda", help="cuda, cpu") |
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| | | parser.add_argument("--ncpu", type=int, default=4, help="cpu cores") |
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| | | parser.add_argument( |
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| | | "--hotword_path", |
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| | | type=str, |
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| | | default="hotwords.txt", |
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| | | help="hot word txt path, only the hot word model works", |
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| | | ) |
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| | | parser.add_argument("--certfile", type=str, default=None, required=False, help="certfile for ssl") |
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| | | parser.add_argument("--keyfile", type=str, default=None, required=False, help="keyfile for ssl") |
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| | | parser.add_argument("--temp_dir", type=str, default="temp_dir/", required=False, help="temp dir") |
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| | | args = parser.parse_args() |
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| | | print("----------- Configuration Arguments -----------") |
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| | | logger.info("----------- Configuration Arguments -----------") |
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| | | for arg, value in vars(args).items(): |
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| | | print("%s: %s" % (arg, value)) |
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| | | print("------------------------------------------------") |
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| | | |
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| | | logger.info("%s: %s" % (arg, value)) |
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| | | logger.info("------------------------------------------------") |
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| | | |
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| | | os.makedirs(args.temp_dir, exist_ok=True) |
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| | | |
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| | | print("model loading") |
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| | | param_dict = {} |
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| | | if args.hotword_path is not None and os.path.exists(args.hotword_path): |
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| | | param_dict['hotword'] = args.hotword_path |
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| | | # asr |
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| | | inference_pipeline_asr = pipeline(task=Tasks.auto_speech_recognition, |
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| | | model=args.asr_model, |
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| | | vad_model=args.vad_model, |
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| | | ngpu=args.ngpu, |
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| | | ncpu=args.ncpu, |
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| | | param_dict=param_dict) |
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| | | print(f'loaded asr models.') |
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| | | |
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| | | if args.punc_model != "": |
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| | | inference_pipeline_punc = pipeline(task=Tasks.punctuation, |
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| | | model=args.punc_model, |
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| | | ngpu=args.ngpu, |
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| | | ncpu=args.ncpu) |
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| | | print(f'loaded pun models.') |
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| | | else: |
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| | | inference_pipeline_punc = None |
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| | | logger.info("model loading") |
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| | | # load funasr model |
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| | | model = AutoModel( |
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| | | model=args.asr_model, |
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| | | model_revision=args.asr_model_revision, |
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| | | vad_model=args.vad_model, |
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| | | vad_model_revision=args.vad_model_revision, |
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| | | punc_model=args.punc_model, |
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| | | punc_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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| | | logger.info("loaded models!") |
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| | | |
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| | | app = FastAPI(title="FunASR") |
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| | | |
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| | | param_dict = {"sentence_timestamp": True, "batch_size_s": 300} |
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| | | if args.hotword_path is not None and os.path.exists(args.hotword_path): |
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| | | with open(args.hotword_path, "r", encoding="utf-8") as f: |
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| | | lines = f.readlines() |
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| | | lines = [line.strip() for line in lines] |
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| | | hotword = " ".join(lines) |
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| | | logger.info(f"热词：{hotword}") |
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| | | param_dict["hotword"] = hotword |
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| | | |
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| | | |
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| | | @app.post("/recognition") |
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| | | async def api_recognition(audio: UploadFile = File(..., description="audio file"), |
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| | | add_pun: int = Body(1, description="add punctuation", embed=True)): |
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| | | suffix = audio.filename.split('.')[-1] |
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| | | audio_path = f'{args.temp_dir}/{str(uuid.uuid1())}.{suffix}' |
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| | | async with aiofiles.open(audio_path, 'wb') as out_file: |
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| | | async def api_recognition(audio: UploadFile = File(..., description="audio file")): |
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| | | suffix = audio.filename.split(".")[-1] |
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| | | audio_path = f"{args.temp_dir}/{str(uuid.uuid1())}.{suffix}" |
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| | | async with aiofiles.open(audio_path, "wb") as out_file: |
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| | | content = await audio.read() |
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| | | await out_file.write(content) |
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| | | audio_bytes, _ = ( |
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| | | ffmpeg.input(audio_path, threads=0) |
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| | | .output("-", format="s16le", acodec="pcm_s16le", ac=1, ar=16000) |
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| | | .run(cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True) |
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| | | try: |
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| | | audio_bytes, _ = ( |
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| | | ffmpeg.input(audio_path, threads=0) |
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| | | .output("-", format="s16le", acodec="pcm_s16le", ac=1, ar=16000) |
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| | | .run(cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True) |
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| | | ) |
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| | | except Exception as e: |
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| | | logger.error(f"读取音频文件发生错误，错误信息：{e}") |
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| | | return {"msg": "读取音频文件发生错误", "code": 1} |
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| | | rec_results = model.generate(input=audio_bytes, is_final=True, **param_dict) |
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| | | # 结果为空 |
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| | | if len(rec_results) == 0: |
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| | | return {"text": "", "sentences": [], "code": 0} |
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| | | elif len(rec_results) == 1: |
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| | | # 解析识别结果 |
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| | | rec_result = rec_results[0] |
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| | | text = rec_result["text"] |
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| | | sentences = [] |
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| | | for sentence in rec_result["sentence_info"]: |
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| | | # 每句话的时间戳 |
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| | | sentences.append( |
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| | | {"text": sentence["text"], "start": sentence["start"], "end": sentence["end"]} |
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| | | ) |
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| | | ret = {"text": text, "sentences": sentences, "code": 0} |
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| | | logger.info(f"识别结果：{ret}") |
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| | | return ret |
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| | | else: |
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| | | logger.info(f"识别结果：{rec_results}") |
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| | | return {"msg": "未知错误", "code": -1} |
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| | | |
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| | | |
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| | | if __name__ == "__main__": |
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| | | uvicorn.run( |
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| | | app, host=args.host, port=args.port, ssl_keyfile=args.keyfile, ssl_certfile=args.certfile |
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| | | ) |
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| | | rec_result = inference_pipeline_asr(audio_in=audio_bytes, param_dict={}) |
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| | | if add_pun: |
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| | | rec_result = inference_pipeline_punc(text_in=rec_result['text'], param_dict={'cache': list()}) |
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| | | ret = {"results": rec_result['text'], "code": 0} |
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| | | print(ret) |
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| | | return ret |
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| | | |
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| | | |
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| | | if __name__ == '__main__': |
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| | | uvicorn.run(app, host=args.host, port=args.port, ssl_keyfile=args.keyfile, ssl_certfile=args.certfile) |
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