def test_str():
from model.configuration import Configuration
config = Configuration()
expected_model = 'phone_call'
expected_language_code = 'hi-IN'
expected_use_enhanced = True
expected_sample_rate_hertz = 48000
expected_audio_channel_count = 5
expected_enable_separate_recognition_per_channel = False
expected_boost = 6
expected_phrases = ['testing', '$ADDRESSNUM']
config.set_model(expected_model)
config.set_language_code(expected_language_code)
config.set_enable_separate_recognition_per_channel(
expected_enable_separate_recognition_per_channel)
config.set_audio_channel_count(expected_audio_channel_count)
config.set_use_enhanced(expected_use_enhanced)
config.set_sample_rate_hertz(expected_sample_rate_hertz)
config.set_speech_context(expected_phrases, expected_boost)
result = config.__str__()
assert isinstance(result, str)
assert expected_model in result
assert expected_language_code in result
assert str(expected_use_enhanced) in result
assert str(expected_sample_rate_hertz) in result
assert str(expected_audio_channel_count) in result
assert str(expected_enable_separate_recognition_per_channel) in result
assert str(expected_boost) in result
def test_set_get_speech_context():
from model.configuration import Configuration
config = Configuration()
expected_boost = 3
expected_phrases = ['foo', 'bar', 'baz']
config.set_speech_context(expected_phrases, expected_boost)
result = config.get_speech_context()
assert result[0]['boost'] == expected_boost
assert result[0]['phrases'] == expected_phrases
def test_create_unique_root_2():
from utilities.utilities import Utilities
from model.configuration import Configuration
from model.nlp import NLPModel
u = Utilities()
configuration = Configuration()
nlp_model = NLPModel()
root = '12345'
configuration.set_model('video')
configuration.set_use_enhanced(False)
configuration.set_language_code('fr_FR')
configuration.set_alternative_language_codes(['en-US', 'ru-RU'])
configuration.set_speech_context('hi', 5)
nlp_model.set_remove_stop_words(True)
nlp_model.set_apply_stemming(False)
nlp_model.set_expand_contractions(True)
nlp_model.set_n2w(True)
result = u.create_unique_root(root, configuration, nlp_model)
expected = '12345_video_fr_FR_alts_applied_speech_adaptation_applied_boost_5_stop_words_removed_contractions_expanded_numbers_converted_2_words'
assert result == expected
if not local_files_path:
ref = gcs.read_ref(cloud_store_uri, root + '.txt')
else:
ref = io_handler.read_file(local_files_path + '/' + root + '.txt')
logger.debug(f'INIT REF: {ref}')
#for speech_run in speech_context_runs:
for boost in boosts:
for language in language_codes:
if boost > 0:
string = f'Running with phrase hints, boost {boost}'
else:
string = 'No speech context applied'
print(string)
logger.debug(string)
if phrases:
configuration.set_speech_context(phrases, boost)
else:
configuration.set_speech_context([], 0)
if alt_run:
configuration.set_alternative_language_codes(alternative_language_codes)
configuration.set_model(model)
configuration.set_sample_rate_hertz(sample_rate_hertz)
configuration.set_language_code(language)
configuration.set_encoding(encoding)
if audio_channel_count > 1:
configuration.set_audio_channel_count(audio_channel_count)
configuration.set_enable_separate_recognition_per_channel(True)
logger.debug(f'CONFIGURATION: {configuration}')
