def test_apply_nlp_options_expand_cont():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = "isn't can't"
options = NLPOptions()
model = NLPModel()
model.set_expand_contractions(True)
result = options.apply_nlp_options(model, hyp)
expected = 'is not cannot'
assert result == expected
def test_apply_nlp_options_n2w_exp():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = "666 don't"
options = NLPOptions()
model = NLPModel()
model.set_n2w(True)
model.set_expand_contractions(True)
result = options.apply_nlp_options(model, hyp)
expected = ' six hundred and sixty-six do not'
assert result == expected
def test_apply_nlp_options_stem_exp():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = "thingy dancing won't"
options = NLPOptions()
model = NLPModel()
model.set_apply_stemming(True)
model.set_expand_contractions(True)
result = options.apply_nlp_options(model, hyp)
expected = 'thingi danc will not '
assert result == expected
def test_stem_stop_exp():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = "don't in the won't didn't isn't raining"
options = NLPOptions()
model = NLPModel()
model.set_expand_contractions(True)
model.set_remove_stop_words(True)
model.set_apply_stemming(True)
result = options.apply_nlp_options(model, hyp)
expected = 'rain '
assert result == expected
def test_apply_nlp_options_stop_n2w_exp():
from utilities.nlp_options import NLPOptions
from model.nlp import NLPModel
hyp = "666 don't in the"
options = NLPOptions()
model = NLPModel()
model.set_n2w(True)
model.set_expand_contractions(True)
model.set_remove_stop_words(True)
result = options.apply_nlp_options(model, hyp)
expected = ' six hundred sixtysix'
assert result == expected
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
configuration = Configuration()
# Turn on punctuation .. why not.. no bearing on WER
configuration.set_enableAutomaticPunctuation(True)
args = parser.parse_args()
no_zeros_for_boost = args.no_zeros_boost
process_each_letter = args.single_word
local_files_path = args.local_files_path
limit = args.limit
cloud_store_uri = args.cloud_store_uri
io_handler.set_result_path(args.local_results_path)
only_transcribe = args.transcriptions_only
nlp_model.set_n2w(args.numbers_to_words)
nlp_model.set_apply_stemming(args.stem)
nlp_model.set_remove_stop_words(args.remove_stop_words)
nlp_model.set_expand_contractions(args.expand)
models = args.models
enhance = args.enhanced
enc = args.encoding
sample_rate_hertz = args.sample_rate_hertz
language_codes = args.langs
phrase_file_path = args.phrase_file
boosts = [int(i) for i in args.boosts]
if not no_zeros_for_boost:
boosts.append(0)
alternative_language_codes = args.alternative_languages
encoding = args.encoding
random_queue = args.random_queue
use_fake_hyp = args.fake_hyp