| | |
|---|
| | | inference_pipeline_vad = pipeline( |
|---|
| | | task=Tasks.voice_activity_detection, |
|---|
| | | model=args.vad_model, |
|---|
| | | model_revision="v1.2.0", |
|---|
| | | model_revision=None, |
|---|
| | | output_dir=None, |
|---|
| | | batch_size=1, |
|---|
| | | mode='online', |
|---|
| | |
|---|
| | | param_dict_vad = {'in_cache': dict(), "is_final": False} |
|---|
| | | |
|---|
| | | # asr |
|---|
| | | param_dict_asr = dict() |
|---|
| | | param_dict_asr = {} |
|---|
| | | # param_dict["hotword"] = "小五 小五月" # 设置热词，用空格隔开 |
|---|
| | | inference_pipeline_asr = pipeline( |
|---|
| | | task=Tasks.auto_speech_recognition, |
|---|
| | |
|---|
| | | ngpu=args.ngpu, |
|---|
| | | ) |
|---|
| | | |
|---|
| | | inference_pipline_punc = pipeline( |
|---|
| | | param_dict_punc = {'cache': list()} |
|---|
| | | inference_pipeline_punc = pipeline( |
|---|
| | | task=Tasks.punctuation, |
|---|
| | | model=args.punc_model, |
|---|
| | | model_revision="v1.0.1", |
|---|
| | | model_revision=None, |
|---|
| | | ngpu=args.ngpu, |
|---|
| | | ) |
|---|
| | | |
|---|
| | |
|---|
| | | |
|---|
| | | def asr(): # 推理 |
|---|
| | | global inference_pipeline2 |
|---|
| | | global speek |
|---|
| | | global speek, param_dict_punc |
|---|
| | | while True: |
|---|
| | | while not speek.empty(): |
|---|
| | | audio_in = speek.get() |
|---|
| | | speek.task_done() |
|---|
| | | if len(audio_in) > 0: |
|---|
| | | rec_result = inference_pipeline_asr(audio_in=audio_in) |
|---|
| | | print(rec_result) |
|---|
| | | if 'text' in rec_result: |
|---|
| | | rec_result = inference_pipeline_punc(text_in=rec_result['text'], param_dict=param_dict_punc) |
|---|
| | | print(rec_result["text"]) |
|---|
| | | time.sleep(0.1) |
|---|
| | | time.sleep(0.1) |
|---|
| | | |
|---|
