| | |
| | | cache["frontend"] = {} |
| | | cache["prev_samples"] = torch.empty(0) |
| | | cache["encoder"] = {} |
| | | |
| | | if kwargs.get("max_end_silence_time") is not None: |
| | | # update the max_end_silence_time |
| | | self.vad_opts.max_end_silence_time = kwargs.get("max_end_silence_time") |
| | | |
| | | windows_detector = WindowDetector(self.vad_opts.window_size_ms, |
| | | self.vad_opts.sil_to_speech_time_thres, |
| | | self.vad_opts.speech_to_sil_time_thres, |
| | |
| | | |
| | | results = [] |
| | | result_i = {"key": key[0], "value": segments} |
| | | if "MODELSCOPE_ENVIRONMENT" in os.environ and os.environ["MODELSCOPE_ENVIRONMENT"] == "eas": |
| | | result_i = json.dumps(result_i) |
| | | # if "MODELSCOPE_ENVIRONMENT" in os.environ and os.environ["MODELSCOPE_ENVIRONMENT"] == "eas": |
| | | # result_i = json.dumps(result_i) |
| | | |
| | | results.append(result_i) |
| | | |