class AudioTester(object):
def __init__(self, samp_rate):
print() # Pad debug messages
self.ww_recognizer = RecognizerLoop().create_mycroft_recognizer(
samp_rate, 'en-us')
self.listener = ResponsiveRecognizer(self.ww_recognizer)
print()
def test_audio(self, file_name):
source = FileMockMicrophone(file_name)
ee = pyee.EventEmitter()
class SharedData:
times_found = 0
def on_found_wake_word():
SharedData.times_found += 1
ee.on('recognizer_loop:record_begin', on_found_wake_word)
try:
while True:
self.listener.listen(source, ee)
except EOFError:
pass
return SharedData.times_found
def testMaxAudioWithBaselineShift(self):
low_base = b"".join(["\x10\x00\x01\x00"] * 100)
higher_base = b"".join(["\x01\x00\x00\x01"] * 100)
source = MockSource()
for i in range(100):
source.stream.inject(low_base)
source.stream.inject(higher_base)
recognizer = ResponsiveRecognizer(None)
sec_per_buffer = float(source.CHUNK) / (source.SAMPLE_RATE *
source.SAMPLE_WIDTH)
test_seconds = 30.0
while test_seconds > 0:
test_seconds -= sec_per_buffer
data = source.stream.read(source.CHUNK)
energy = recognizer.calc_energy(data, source.SAMPLE_WIDTH)
recognizer.adjust_threshold(energy, sec_per_buffer)
higher_base_energy = audioop.rms(higher_base, source.SAMPLE_WIDTH)
# after recalibration (because of max audio length) new threshold
# should be >= 1.5 * higher_base_energy
delta_below_threshold = (
recognizer.energy_threshold - higher_base_energy)
min_delta = higher_base_energy * .5
assert abs(delta_below_threshold - min_delta) < 1
class AudioTester(object):
def __init__(self, samp_rate):
print # Pad debug messages
self.ww_recognizer = LocalRecognizer(samp_rate, 'en-us')
self.listener = ResponsiveRecognizer(self.ww_recognizer)
print
speech_logger.setLevel(100) # Disables logging to clean output
def test_audio(self, file_name):
source = FileMockMicrophone(file_name)
ee = pyee.EventEmitter()
class SharedData:
times_found = 0
def on_found_wake_word():
SharedData.times_found += 1
ee.on('recognizer_loop:record_begin', on_found_wake_word)
try:
while True:
self.listener.listen(source, ee)
except EOFError:
pass
return SharedData.times_found
def __init__(self, samp_rate):
print # Pad debug messages
self.ww_recognizer = RecognizerLoop().create_mycroft_recognizer(
samp_rate, 'en-us')
self.listener = ResponsiveRecognizer(self.ww_recognizer)
print
speech_logger.setLevel(100) # Disables logging to clean output
def _load_config(self):
"""
Load configuration parameters from configuration
"""
config = Configuration.get()
self.config_core = config
self._config_hash = hash(str(config))
self.lang = config.get('lang')
self.config = config.get('listener')
rate = self.config.get('sample_rate')
device_index = self.config.get('device_index')
self.microphone = MutableMicrophone(device_index,
rate,
mute=self.mute_calls > 0)
# FIXME - channels are not been used
self.microphone.CHANNELS = self.config.get('channels')
self.wakeword_recognizer = self.create_wake_word_recognizer()
# TODO - localization
self.wakeup_recognizer = self.create_wakeup_recognizer()
self.responsive_recognizer = ResponsiveRecognizer(
self.wakeword_recognizer)
self.state = RecognizerLoopState()
def __init__(self, samp_rate):
print() # Pad debug messages
self.ww_recognizer = RecognizerLoop().create_wake_word_recognizer()
self.listener = ResponsiveRecognizer(self.ww_recognizer)
self.listener.config['confirm_listening'] = False
print()
def __init__(self, samp_rate):
print() # Pad debug messages
self.ww_recognizer = RecognizerLoop().create_mycroft_recognizer(
samp_rate, 'en-us')
self.listener = ResponsiveRecognizer(self.ww_recognizer)
print()
def __init__(self, samp_rate):
self.ww_recognizer = LocalRecognizer(samp_rate, 'en-us')
self.listener = ResponsiveRecognizer(self.ww_recognizer)
speech_logger.setLevel(100) # Disables logging to clean output
