class AudioConsumerTest(unittest.TestCase):
"""
AudioConsumerTest
"""
def setUp(self):
self.loop = RecognizerLoop()
self.queue = Queue()
self.recognizer = MockRecognizer()
self.consumer = AudioConsumer(self.loop.state, self.queue, self.loop,
MycroftSTT(),
self.loop.wakeup_recognizer,
self.loop.wakeword_recognizer)
def __create_sample_from_test_file(self, sample_name):
root_dir = dirname(dirname(dirname(__file__)))
filename = join(root_dir, 'unittests', 'client', 'data',
sample_name + '.wav')
wavfile = WavFile(filename)
with wavfile as source:
return AudioData(source.stream.read(), wavfile.SAMPLE_RATE,
wavfile.SAMPLE_WIDTH)
def test_word_extraction(self):
"""
This is intended to test the extraction of the word: ``mycroft``.
The values for ``ideal_begin`` and ``ideal_end`` were found using an
audio tool like Audacity and they represent a sample value position of
the audio. ``tolerance`` is an acceptable margin error for the distance
between the ideal and actual values found by the ``WordExtractor``
"""
# TODO: implement WordExtractor test without relying on the listener
return
audio = self.__create_sample_from_test_file('weather_mycroft')
self.queue.put(audio)
tolerance = 4000
ideal_begin = 70000
ideal_end = 92000
monitor = {}
self.recognizer.set_transcriptions(["what's the weather next week"])
def wakeword_callback(message):
monitor['pos_begin'] = message.get('pos_begin')
monitor['pos_end'] = message.get('pos_end')
self.loop.once('recognizer_loop:wakeword', wakeword_callback)
self.consumer.read()
actual_begin = monitor.get('pos_begin')
self.assertIsNotNone(actual_begin)
diff = abs(actual_begin - ideal_begin)
self.assertTrue(diff <= tolerance,
str(diff) + " is not less than " + str(tolerance))
actual_end = monitor.get('pos_end')
self.assertIsNotNone(actual_end)
diff = abs(actual_end - ideal_end)
self.assertTrue(diff <= tolerance,
str(diff) + " is not less than " + str(tolerance))
@unittest.skip('Disabled while unittests are brought upto date')
def test_wakeword_in_beginning(self):
self.queue.put(self.__create_sample_from_test_file('weather_mycroft'))
self.recognizer.set_transcriptions(["what's the weather next week"])
monitor = {}
def callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:utterance', callback)
self.consumer.read()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 1)
self.assertEquals("what's the weather next week", utterances[0])
@unittest.skip('Disabled while unittests are brought upto date')
def test_wakeword(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
self.recognizer.set_transcriptions(["silence"])
monitor = {}
def callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:utterance', callback)
self.consumer.read()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 1)
self.assertEquals("silence", utterances[0])
def test_ignore_wakeword_when_sleeping(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
self.recognizer.set_transcriptions(["not detected"])
self.loop.sleep()
monitor = {}
def wakeword_callback(message):
monitor['wakeword'] = message.get('utterance')
self.loop.once('recognizer_loop:wakeword', wakeword_callback)
self.consumer.read()
self.assertIsNone(monitor.get('wakeword'))
self.assertTrue(self.loop.state.sleeping)
def test_wakeup(self):
self.queue.put(self.__create_sample_from_test_file('mycroft_wakeup'))
self.loop.sleep()
self.consumer.read()
self.assertFalse(self.loop.state.sleeping)
@unittest.skip('Disabled while unittests are brought upto date')
def test_stop(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
self.consumer.read()
self.queue.put(self.__create_sample_from_test_file('stop'))
self.recognizer.set_transcriptions(["stop"])
monitor = {}
def utterance_callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:utterance', utterance_callback)
self.consumer.read()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 1)
self.assertEquals("stop", utterances[0])
@unittest.skip('Disabled while unittests are brought upto date')
def test_record(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
self.consumer.read()
self.queue.put(self.__create_sample_from_test_file('record'))
self.recognizer.set_transcriptions(["record"])
monitor = {}
def utterance_callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:utterance', utterance_callback)
self.consumer.read()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 1)
self.assertEquals("record", utterances[0])
class AudioConsumerTest(unittest.TestCase):
"""
AudioConsumerTest
"""
def setUp(self):
self.loop = RecognizerLoop()
self.queue = Queue()
self.recognizer = MockRecognizer()
self.consumer = AudioConsumer(
self.loop.state,
self.queue,
self.loop,
self.loop.wakeup_recognizer,
self.loop.ww_recognizer,
RemoteRecognizerWrapperFactory.wrap_recognizer(self.recognizer, 'google'),
self.loop.wakeup_prefixes,
self.loop.wakeup_words)
def __create_sample_from_test_file(self, sample_name):
root_dir = dirname(dirname(dirname(__file__)))
filename = join(root_dir, 'test', 'client', 'data', sample_name + '.wav')
wavfile = WavFile(filename)
with wavfile as source:
return AudioData(source.stream.read(), wavfile.SAMPLE_RATE, wavfile.SAMPLE_WIDTH)
def test_audio_pos_front_back(self):
audio = self.__create_sample_from_test_file('mycroft_in_utterance')
self.queue.put(audio)
TRUE_POS_BEGIN = 69857 + int(WakewordExtractor.TRIM_SECONDS * audio.sample_rate * audio.sample_width)
TRUE_POS_END = 89138 - int(WakewordExtractor.TRIM_SECONDS * audio.sample_rate * audio.sample_width)
TOLERANCE_RANGE_FRAMES = WakewordExtractor.MAX_ERROR_SECONDS * audio.sample_rate * audio.sample_width
monitor = {}
self.recognizer.set_transcriptions(["what's the weather next week", ""])
def wakeword_callback(message):
monitor['pos_begin'] = message.get('pos_begin')
monitor['pos_end'] = message.get('pos_end')
self.loop.once('recognizer_loop:wakeword', wakeword_callback)
self.consumer.try_consume_audio()
pos_begin = monitor.get('pos_begin')
self.assertIsNotNone(pos_begin)
diff = abs(pos_begin - TRUE_POS_BEGIN)
self.assertTrue(diff <= TOLERANCE_RANGE_FRAMES, str(diff) + " is not less than " + str(TOLERANCE_RANGE_FRAMES))
pos_end = monitor.get('pos_end')
self.assertIsNotNone(pos_end)
diff = abs(pos_end - TRUE_POS_END)
self.assertTrue(diff <= TOLERANCE_RANGE_FRAMES, str(diff) + " is not less than " + str(TOLERANCE_RANGE_FRAMES))
def test_wakeword_in_beginning(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
monitor = {}
self.recognizer.set_transcriptions(["what's the weather next week", ""])
def callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:utterance', callback)
self.consumer.try_consume_audio()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 1)
self.assertEquals("what's the weather next week", utterances[0])
def test_wakeword_in_phrase(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
monitor = {}
self.recognizer.set_transcriptions(["he can do other stuff too", "what's the weather in cincinnati"])
def callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:utterance', callback)
self.consumer.try_consume_audio()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 2)
self.assertEquals("he can do other stuff too", utterances[0])
self.assertEquals("what's the weather in cincinnati", utterances[1])
def test_call_and_response(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
monitor = {}
self.recognizer.set_transcriptions(["mycroft",""])
def wakeword_callback(message):
monitor['wakeword'] = message.get('utterance')
def utterance_callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:wakeword', wakeword_callback)
self.consumer.try_consume_audio()
self.assertIsNotNone(monitor.get('wakeword'))
self.queue.put(self.__create_sample_from_test_file('mycroft'))
self.recognizer.set_transcriptions(["what's the weather next week", ""])
self.loop.once('recognizer_loop:utterance', utterance_callback)
self.consumer.try_consume_audio()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 1)
self.assertEquals("what's the weather next week", utterances[0])
def test_ignore_wakeword_when_sleeping(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
self.loop.sleep()
monitor = {}
self.recognizer.set_transcriptions(["", ""])
def wakeword_callback(message):
monitor['wakeword'] = message.get('utterance')
self.loop.once('recognizer_loop:wakeword', wakeword_callback)
self.consumer.try_consume_audio()
self.assertIsNone(monitor.get('wakeword'))
self.assertTrue(self.loop.state.sleeping)
class AudioConsumerTest(unittest.TestCase):
"""
AudioConsumerTest
"""
def setUp(self):
self.loop = RecognizerLoop()
self.queue = Queue()
self.recognizer = MockRecognizer()
self.consumer = AudioConsumer(
self.loop.state,
self.queue,
self.loop,
self.loop.wakeup_recognizer,
self.loop.mycroft_recognizer,
RemoteRecognizerWrapperFactory.wrap_recognizer(
self.recognizer, 'google'))
def __create_sample_from_test_file(self, sample_name):
root_dir = dirname(dirname(dirname(__file__)))
filename = join(
root_dir, 'test', 'client', 'data', sample_name + '.wav')
wavfile = WavFile(filename)
with wavfile as source:
return AudioData(
source.stream.read(), wavfile.SAMPLE_RATE,
wavfile.SAMPLE_WIDTH)
def test_word_extraction(self):
"""
This is intended to test the extraction of the word: ``mycroft``.
The values for ``ideal_begin`` and ``ideal_end`` were found using an
audio tool like Audacity and they represent a sample value position of
the audio. ``tolerance`` is an acceptable margin error for the distance
between the ideal and actual values found by the ``WordExtractor``
"""
# TODO: implement WordExtractor test without relying on the listener
return
audio = self.__create_sample_from_test_file('weather_mycroft')
self.queue.put(audio)
tolerance = 4000
ideal_begin = 70000
ideal_end = 92000
monitor = {}
self.recognizer.set_transcriptions(["what's the weather next week"])
def wakeword_callback(message):
monitor['pos_begin'] = message.get('pos_begin')
monitor['pos_end'] = message.get('pos_end')
self.loop.once('recognizer_loop:wakeword', wakeword_callback)
self.consumer.read_audio()
actual_begin = monitor.get('pos_begin')
self.assertIsNotNone(actual_begin)
diff = abs(actual_begin - ideal_begin)
self.assertTrue(
diff <= tolerance,
str(diff) + " is not less than " + str(tolerance))
actual_end = monitor.get('pos_end')
self.assertIsNotNone(actual_end)
diff = abs(actual_end - ideal_end)
self.assertTrue(
diff <= tolerance,
str(diff) + " is not less than " + str(tolerance))
def test_wakeword_in_beginning(self):
self.queue.put(self.__create_sample_from_test_file('weather_mycroft'))
self.recognizer.set_transcriptions(["what's the weather next week"])
monitor = {}
def callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:utterance', callback)
self.consumer.read_audio()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 1)
self.assertEquals("what's the weather next week", utterances[0])
def test_wakeword(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
self.recognizer.set_transcriptions(["silence"])
monitor = {}
def callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:utterance', callback)
self.consumer.read_audio()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 1)
self.assertEquals("silence", utterances[0])
def test_ignore_wakeword_when_sleeping(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
self.recognizer.set_transcriptions(["not detected"])
self.loop.sleep()
monitor = {}
def wakeword_callback(message):
monitor['wakeword'] = message.get('utterance')
self.loop.once('recognizer_loop:wakeword', wakeword_callback)
self.consumer.read_audio()
self.assertIsNone(monitor.get('wakeword'))
self.assertTrue(self.loop.state.sleeping)
def test_wakeup(self):
self.queue.put(self.__create_sample_from_test_file('mycroft_wakeup'))
self.loop.sleep()
self.consumer.read_audio()
self.assertFalse(self.loop.state.sleeping)
def test_stop(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
self.consumer.read_audio()
self.queue.put(self.__create_sample_from_test_file('stop'))
self.recognizer.set_transcriptions(["stop"])
monitor = {}
def utterance_callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:utterance', utterance_callback)
self.consumer.read_audio()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 1)
self.assertEquals("stop", utterances[0])
def test_record(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
self.consumer.read_audio()
self.queue.put(self.__create_sample_from_test_file('record'))
self.recognizer.set_transcriptions(["record"])
monitor = {}
def utterance_callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:utterance', utterance_callback)
self.consumer.read_audio()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 1)
self.assertEquals("record", utterances[0])
class AudioConsumerTest(unittest.TestCase):
"""
AudioConsumerTest
"""
def setUp(self):
self.loop = RecognizerLoop()
self.queue = Queue()
self.recognizer = MockRecognizer()
self.consumer = AudioConsumer(
self.loop.state, self.queue, self.loop,
self.loop.wakeup_recognizer, self.loop.ww_recognizer,
RemoteRecognizerWrapperFactory.wrap_recognizer(
self.recognizer,
'google'), self.loop.wakeup_prefixes, self.loop.wakeup_words)
def __create_sample_from_test_file(self, sample_name):
root_dir = dirname(dirname(dirname(__file__)))
filename = join(root_dir, 'test', 'client', 'data',
sample_name + '.wav')
wavfile = WavFile(filename)
with wavfile as source:
return AudioData(source.stream.read(), wavfile.SAMPLE_RATE,
wavfile.SAMPLE_WIDTH)
def test_audio_pos_front_back(self):
audio = self.__create_sample_from_test_file('mycroft_in_utterance')
self.queue.put(audio)
TRUE_POS_BEGIN = 69857 + int(WakewordExtractor.TRIM_SECONDS *
audio.sample_rate * audio.sample_width)
TRUE_POS_END = 89138 - int(WakewordExtractor.TRIM_SECONDS *
audio.sample_rate * audio.sample_width)
TOLERANCE_RANGE_FRAMES = (WakewordExtractor.MAX_ERROR_SECONDS *
audio.sample_rate * audio.sample_width)
monitor = {}
self.recognizer.set_transcriptions(
["what's the weather next week", ""])
def wakeword_callback(message):
monitor['pos_begin'] = message.get('pos_begin')
monitor['pos_end'] = message.get('pos_end')
self.loop.once('recognizer_loop:wakeword', wakeword_callback)
self.consumer.try_consume_audio()
pos_begin = monitor.get('pos_begin')
self.assertIsNotNone(pos_begin)
diff = abs(pos_begin - TRUE_POS_BEGIN)
self.assertTrue(
diff <= TOLERANCE_RANGE_FRAMES,
str(diff) + " is not less than " + str(TOLERANCE_RANGE_FRAMES))
pos_end = monitor.get('pos_end')
self.assertIsNotNone(pos_end)
diff = abs(pos_end - TRUE_POS_END)
self.assertTrue(
diff <= TOLERANCE_RANGE_FRAMES,
str(diff) + " is not less than " + str(TOLERANCE_RANGE_FRAMES))
def test_wakeword_in_beginning(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
monitor = {}
self.recognizer.set_transcriptions(
["what's the weather next week", ""])
def callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:utterance', callback)
self.consumer.try_consume_audio()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 1)
self.assertEquals("what's the weather next week", utterances[0])
def test_wakeword_in_phrase(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
monitor = {}
self.recognizer.set_transcriptions(
["he can do other stuff too", "what's the weather in cincinnati"])
def callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:utterance', callback)
self.consumer.try_consume_audio()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 2)
self.assertEquals("he can do other stuff too", utterances[0])
self.assertEquals("what's the weather in cincinnati", utterances[1])
def test_call_and_response(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
monitor = {}
self.recognizer.set_transcriptions(["mycroft", ""])
def wakeword_callback(message):
monitor['wakeword'] = message.get('utterance')
def utterance_callback(message):
monitor['utterances'] = message.get('utterances')
self.loop.once('recognizer_loop:wakeword', wakeword_callback)
self.consumer.try_consume_audio()
self.assertIsNotNone(monitor.get('wakeword'))
self.queue.put(self.__create_sample_from_test_file('mycroft'))
self.recognizer.set_transcriptions(
["what's the weather next week", ""])
self.loop.once('recognizer_loop:utterance', utterance_callback)
self.consumer.try_consume_audio()
utterances = monitor.get('utterances')
self.assertIsNotNone(utterances)
self.assertTrue(len(utterances) == 1)
self.assertEquals("what's the weather next week", utterances[0])
def test_ignore_wakeword_when_sleeping(self):
self.queue.put(self.__create_sample_from_test_file('mycroft'))
self.loop.sleep()
monitor = {}
self.recognizer.set_transcriptions(["", ""])
def wakeword_callback(message):
monitor['wakeword'] = message.get('utterance')
self.loop.once('recognizer_loop:wakeword', wakeword_callback)
self.consumer.try_consume_audio()
self.assertIsNone(monitor.get('wakeword'))
self.assertTrue(self.loop.state.sleeping)