def word_parser(final_callback=None):
global model
global datahandler
model = Model()
datahandler = DataHandler(noActualLoad=True)
for i, word in enumerate(datahandler.getClasses()):
current_word_prob[word] = 0
capture_audio(callback_word, final_callback)
def main():
config = Config()
parser = argparse.ArgumentParser()
parser.add_argument('-td',
'--test-dataset',
help='Walk through dataset \
and test while preprocessing',
action='store_true')
parser.add_argument('-e', '--execute', help='Execute', action='store_true')
parser.add_argument('-t',
'--train',
help='Train Model',
action='store_true')
parser.add_argument('-wp',
'--word-parser',
help='Listen to microphone parse the word',
action='store_true')
parser.add_argument('-p', '--predict', help='Predict Audiofile', nargs='+')
args = parser.parse_args()
if args.test_dataset:
datahandler = DataHandler()
print("Test Passed")
return
if args.execute:
from event_handler import EventHandler
eh = EventHandler()
word_parser(eh)
if args.train:
model = Model()
model.train()
if args.predict:
model = Model()
datahandler = DataHandler(noActualLoad=True)
result_prob = model.predict(args.predict, datahandler.getClasses())
for fname, rp in zip(args.predict, result_prob):
print("%s\t%s\twith Probabity %f" % (fname, rp[0], rp[1]))
if args.word_parser:
word_parser()
