DeepSpeech/native_client/test/concurrent_streams.py
2020-02-12 10:13:02 +01:00

54 lines
1.6 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
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('--scorer', nargs='?',
help='Path to the external scorer file')
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)
if args.scorer:
ds.enableExternalScorer(args.scorer)
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()
stream2 = ds.createStream()
splits1 = np.array_split(audio1, 10)
splits2 = np.array_split(audio2, 10)
for part1, part2 in zip(splits1, splits2):
stream1.feedAudioContent(part1)
stream2.feedAudioContent(part2)
print(stream1.finishStream())
print(stream2.finishStream())
if __name__ == '__main__':
main()