def calc_thresh(self, model_file, samples_folder):
from precise_runner import PreciseEngine
engine = PreciseEngine(self.engine_exe, model_file, self.chunk_size)
engine.start()
all_max = []
for sample_file in glob(join(samples_folder, '*.wav')):
with wave.open(sample_file, 'r') as wr:
frames = wr.readframes(wr.getnframes() - 1)
chop = len(frames) % self.chunk_size
max_pred = float('-inf')
for i in range(10):
engine.get_prediction(b'\0' * self.chunk_size)
for pos in range(chop + self.chunk_size,
len(frames) + 1, self.chunk_size):
pred = engine.get_prediction(frames[pos - self.chunk_size:pos])
max_pred = max(max_pred, pred)
print('MAX PRED:', max_pred)
all_max.append(max_pred)
av_max = sum(all_max) / len(all_max)
stddev = sqrt(sum([(i - av_max)**2 for i in all_max]))
good_max = [i for i in all_max if i > av_max - stddev]
good_av = sum(good_max) / len(good_max)
stddev = sqrt(sum([(i - good_av)**2 for i in good_max]))
thresh = good_av - stddev
return thresh
def handle_train(self, subfolder, dialog_file):
if self.handle_precise_download():
return
name = self.get_response('ask.speaker.name',
validator=lambda x: x and len(x.split()) < 4,
on_fail=lambda utterance: self.dialog_renderer
.render('name.error', {'name': utterance}))
if not name:
return
self.speak_dialog(dialog_file)
wait_while_speaking()
from precise_runner import PreciseEngine
engine = PreciseEngine(self.engine_exe, self.model_file,
self.chunk_size)
engine.start()
recording = self.record_wav()
with wave.open(recording, 'r') as wr:
orig_params = wr.getparams()
frames = wr.readframes(wr.getnframes() - 1)
ww_positions = self.extract_ww_positions(frames, engine)
engine.stop()
samples_folder = join(self.folder, 'samples', name)
samples_raw_folder = join(samples_folder, 'not-wake-word')
makedirs(samples_raw_folder, exist_ok=True)
self.split_recording(frames, samples_raw_folder, ww_positions,
orig_params)
self.speak_dialog('recording.complete')
models_folder = join(self.folder, 'user-models')
makedirs(models_folder, exist_ok=True)
model_file = join(models_folder,
'{}.{}.net'.format('hey-mycroft', name))
self.transfer_train(samples_folder, model_file)
self.speak_dialog('model.confirm')
thresh = self.calc_thresh(model_file, samples_raw_folder)
print("THRESH:", thresh)