def __init__(self, model_file, ken_lm_file, context_length=10):
self.listener = Listener(sample_rate=8000)
self.model = torch.jit.load(model_file)
self.model.eval().to('cpu') #run on cpu
self.featurizer = get_featurizer(8000)
self.audio_q = list()
self.hidden = (torch.zeros(1, 1, 1024), torch.zeros(1, 1, 1024))
self.beam_results = ""
self.out_args = None
self.beam_search = CTCBeamDecoder(beam_size=100,
kenlm_path=ken_lm_file)
self.context_length = context_length * 50 # multiply by 50 because each 50 from output frame is 1 second
self.start = False
def __init__(self, model_file):
self.listener = Listener(sample_rate=8000, record_seconds=2)
self.model = torch.jit.load(model_file)
self.model.eval().to('cpu') #run on cpu
self.featurizer = get_featurizer(sample_rate=8000)
self.audio_q = list()