if __name__ == "__main__":
decoder = Decoder(MODEL_PATH)
file_name = os.path.join(os.path.dirname(__file__), 'eleven.wav')
data = wave.open(file_name)
n_decoded = 0
while True:
frames = data.readframes(8000)
if len(frames) == 0:
break
decoder.accept_audio(frames)
n_decoded += decoder.decode(8000)
if n_decoded > 0:
prob, word_ids = decoder.get_best_path()
# ivec = decoder.get_ivector()
print('Hypothesis: "%s" (speaker finished speaking: %s)' % (
word_ids_to_str_hyp(decoder, word_ids),
decoder.endpoint_detected(),
))
decoder.input_finished()
print('Final hypothesis: "%s"' % word_ids_to_str_hyp(decoder, word_ids))
decoder.finalize_decoding()
p, lat = decoder.get_lattice()
if __name__ == "__main__":
decoder = Decoder(MODEL_PATH)
file_name = os.path.join(os.path.dirname(__file__), 'eleven.wav')
data = wave.open(file_name)
n_decoded = 0
while True:
frames = data.readframes(8000)
if len(frames) == 0:
break
decoder.accept_audio(frames)
n_decoded += decoder.decode(8000)
if n_decoded > 0:
prob, word_ids = decoder.get_best_path()
# ivec = decoder.get_ivector()
print('Hypothesis: "%s" (speaker finished speaking: %s)' % (word_ids_to_str_hyp(decoder, word_ids), decoder.endpoint_detected(), ))
decoder.input_finished()
print('Final hypothesis: "%s"' % word_ids_to_str_hyp(decoder, word_ids))
decoder.finalize_decoding()
p, lat = decoder.get_lattice()
print ('Resulting lattice:')
for state in lat.states:
import struct
from os.path import basename
inputdir = sys.argv[1]
scratchdir = sys.argv[2]
resourcedir = sys.argv[3]
outdir = sys.argv[4]
os.system('mkdir -p ' + scratchdir)
# Load speech recognition model from "asr_model_dir" directory.
for inputfile in glob.glob(inputdir + '/*.wav'):
decoder = Decoder(resourcedir + "/asr_model_dir_nnet3")
file_id = basename(inputfile)
os.system('sox ' + inputfile + ' -e signed-integer -r 16000 -b 16 -c 1 ' +
scratchdir + file_id + '.wav')
# Load audio frames from input wav file.
data = wave.open(scratchdir + file_id + '.wav')
frames = data.readframes(data.getnframes())
# Feed the audio data to the decoder.
decoder.accept_audio(frames)
decoder.decode(data.getnframes())
decoder.input_finished()
# Get and print the best hypothesis.
prob, word_ids = decoder.get_best_path()
output_string = " ".join(map(decoder.get_word, word_ids))
os.system('echo ' + output_string + ' > ' + outdir + '/' + file_id +
'.txt')