mirror of
https://github.com/kkroening/ffmpeg-python.git
synced 2025-04-05 04:22:51 +08:00
57 lines
1.7 KiB
Python
Executable File
57 lines
1.7 KiB
Python
Executable File
#!/usr/bin/env python
|
|
from __future__ import unicode_literals, print_function
|
|
from google.cloud import speech
|
|
from google.cloud.speech import enums
|
|
from google.cloud.speech import types
|
|
import argparse
|
|
import ffmpeg
|
|
import logging
|
|
import sys
|
|
|
|
|
|
logging.basicConfig(level=logging.INFO, format='%(message)s')
|
|
logger = logging.getLogger(__file__)
|
|
logger.setLevel(logging.INFO)
|
|
|
|
|
|
parser = argparse.ArgumentParser(description='Convert speech audio to text using Google Speech API')
|
|
parser.add_argument('in_filename', help='Input filename (`-` for stdin)')
|
|
|
|
|
|
def decode_audio(in_filename, **input_kwargs):
|
|
try:
|
|
out, err = (ffmpeg
|
|
.input(in_filename, **input_kwargs)
|
|
.output('-', format='s16le', acodec='pcm_s16le', ac=1, ar='16k')
|
|
.overwrite_output()
|
|
.run(capture_stdout=True, capture_stderr=True)
|
|
)
|
|
except ffmpeg.Error as e:
|
|
print(f"$ {e.cmdline}\n{e.stderr.decode()}", file=sys.stderr)
|
|
sys.exit(1)
|
|
return out
|
|
|
|
|
|
def get_transcripts(audio_data):
|
|
client = speech.SpeechClient()
|
|
audio = types.RecognitionAudio(content=audio_data)
|
|
config = types.RecognitionConfig(
|
|
encoding=enums.RecognitionConfig.AudioEncoding.LINEAR16,
|
|
sample_rate_hertz=16000,
|
|
language_code='en-US'
|
|
)
|
|
response = client.recognize(config, audio)
|
|
return [result.alternatives[0].transcript for result in response.results]
|
|
|
|
|
|
def transcribe(in_filename):
|
|
audio_data = decode_audio(in_filename)
|
|
transcripts = get_transcripts(audio_data)
|
|
for transcript in transcripts:
|
|
print(repr(transcript.encode('utf-8')))
|
|
|
|
|
|
if __name__ == '__main__':
|
|
args = parser.parse_args()
|
|
transcribe(args.in_filename)
|