DeepSpeech/native_client/test/concurrent_streams.py
2019-09-09 12:03:14 +02:00

70 lines
2.3 KiB
Python

#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function
import argparse
import numpy as np
import wave
from deepspeech import Model
# These constants control the beam search decoder
# Beam width used in the CTC decoder when building candidate transcriptions
BEAM_WIDTH = 500
# The alpha hyperparameter of the CTC decoder. Language Model weight
LM_ALPHA = 0.75
# The beta hyperparameter of the CTC decoder. Word insertion bonus.
LM_BETA = 1.85
def main():
parser = argparse.ArgumentParser(description='Running DeepSpeech inference.')
parser.add_argument('--model', required=True,
help='Path to the model (protocol buffer binary file)')
parser.add_argument('--alphabet', required=True,
help='Path to the configuration file specifying the alphabet used by the network')
parser.add_argument('--lm', nargs='?',
help='Path to the language model binary file')
parser.add_argument('--trie', nargs='?',
help='Path to the language model trie file created with native_client/generate_trie')
parser.add_argument('--audio1', required=True,
help='First audio file to use in interleaved streams')
parser.add_argument('--audio2', required=True,
help='Second audio file to use in interleaved streams')
args = parser.parse_args()
ds = Model(args.model, args.alphabet, BEAM_WIDTH)
if args.lm and args.trie:
ds.enableDecoderWithLM(args.lm, args.trie, LM_ALPHA, LM_BETA)
fin = wave.open(args.audio1, 'rb')
fs1 = fin.getframerate()
audio1 = np.frombuffer(fin.readframes(fin.getnframes()), np.int16)
fin.close()
fin = wave.open(args.audio2, 'rb')
fs2 = fin.getframerate()
audio2 = np.frombuffer(fin.readframes(fin.getnframes()), np.int16)
fin.close()
stream1 = ds.createStream(sample_rate=fs1)
stream2 = ds.createStream(sample_rate=fs2)
splits1 = np.array_split(audio1, 10)
splits2 = np.array_split(audio2, 10)
for part1, part2 in zip(splits1, splits2):
ds.feedAudioContent(stream1, part1)
ds.feedAudioContent(stream2, part2)
print(ds.finishStream(stream1))
print(ds.finishStream(stream2))
if __name__ == '__main__':
main()