| from espnet2.bin.asr_inference import Speech2Text | |
| import resampy | |
| from espnet_model_zoo.downloader import ModelDownloader | |
| class DemoASR: | |
| def __init__(self, model_path, device): | |
| model_file = 'asr_improved_tts-phn_en.zip' | |
| d = ModelDownloader() | |
| self.speech2text = Speech2Text( | |
| **d.download_and_unpack(str(model_path / model_file)), | |
| device=str(device), | |
| minlenratio=0.0, | |
| maxlenratio=0.0, | |
| ctc_weight=0.4, | |
| beam_size=15, | |
| batch_size=1, | |
| nbest=1 | |
| ) | |
| def recognize_speech(self, audio, sr): | |
| if len(audio.shape) == 2: | |
| audio = audio.T[0] | |
| speech = resampy.resample(audio, sr, 16000) | |
| nbests = self.speech2text(speech) | |
| text, *_ = nbests[0] | |
| return text | |