def __init__(self, model, filter_length, sample_rate, framesize,
frameshift, usehamming, preemcoef, numchans, ceplifter,
numceps, enormalise, zmeansource, usepower, usec0, usecmn,
usedelta, useacc, n_last_frames, n_prev_frames, lofreq,
hifreq, mel_banks_only):
self.audio_recorded_in = []
self.ffnn = TheanoFFNN()
self.ffnn.load(model)
self.log_probs_speech = deque(maxlen=filter_length)
self.log_probs_sil = deque(maxlen=filter_length)
self.last_decision = 0.0
self.front_end = MFCCFrontEnd(sample_rate, framesize, usehamming,
preemcoef, numchans, ceplifter, numceps,
enormalise, zmeansource, usepower, usec0,
usecmn, usedelta, useacc,
n_last_frames + n_prev_frames, lofreq,
hifreq, mel_banks_only)
self.samplerate = sample_rate
self.framesize = framesize
self.frameshift = frameshift
def __init__(self, cfg):
self.cfg = cfg
self.audio_recorded_in = []
self.ffnn = TheanoFFNN()
self.ffnn.load(self.cfg['model'])
self.log_probs_speech = deque(maxlen=self.cfg['filter_length'])
self.log_probs_sil = deque(maxlen=self.cfg['filter_length'])
self.last_decision = 0.0
if self.cfg['frontend'] == 'MFCC':
self.front_end = MFCCFrontEnd(
self.cfg['sample_rate'], self.cfg['framesize'],
self.cfg['usehamming'], self.cfg['preemcoef'],
self.cfg['numchans'], self.cfg['ceplifter'],
self.cfg['numceps'], self.cfg['enormalise'],
self.cfg['zmeansource'], self.cfg['usepower'],
self.cfg['usec0'], self.cfg['usecmn'], self.cfg['usedelta'],
self.cfg['useacc'],
self.cfg['n_last_frames'] + self.cfg['n_prev_frames'],
self.cfg['lofreq'], self.cfg['hifreq'],
self.cfg['mel_banks_only'])
else:
raise ASRException('Unsupported frontend: %s' %
(self.cfg['frontend'], ))