I am working through the provided code snippets from the Google Speech API, found here. The code should be enough to convert a .wav file into transcribed text.
The block of interest is here:
def transcribe_file(speech_file):
"""Transcribe the given audio file."""
from google.cloud import speech
speech_client = speech.Client()
with io.open(speech_file, 'rb') as audio_file:
content = audio_file.read()
audio_sample = speech_client.sample(
content=content,
source_uri=None,
encoding='LINEAR16',
sample_rate_hertz=16000)
alternatives = audio_sample.recognize('en-US')
for alternative in alternatives:
print('Transcript: {}'.format(alternative.transcript))
First, I think perhaps the code is old, and sample_rate_hertz=16000 had to be changed to sample_rate=16000.
After that, I got an error for this line:
alternatives = audio_sample.recognize('en-US')
which read
AttributeError: 'Sample' object has no attribute 'recognize'
I am curious about how to rectify this. I can't seem to find any documentation on this method. Maybe it needs to be replaced too.
You nead to read file as binary, then use service.speech().syncrecognize with a body argument (dict), which contain all required arguments like :
May you try something like:
with open(speech_file, 'rb') as speech:
speech_content = base64.b64encode(speech.read())
service = get_speech_service()
service_request = service.speech().syncrecognize(
body={
'config': {
'encoding': 'LINEAR16', # raw 16-bit signed LE samples
'sampleRate': 16000, # 16 khz
'languageCode': 'en-US', # a BCP-47 language tag
},
'audio': {
'content': speech_content.decode('UTF-8')
}
})
response = service_request.execute()
print(json.dumps(response))
Please take a look here, because there is a similar working example.