def recognize(pub):
with cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443)) as service:
# For streaming audio from the microphone, there are three threads.
# First, a thread that collects audio data as it comes in
# print("entered make_channel")
with record_audio(RATE, CHUNK) as buffered_audio_data:
# print("entered record_audio")
# Second, a thread that sends requests with that data
# requests is a generator
# when we have a new_context, we should make a new generator
requests = request_stream(buffered_audio_data, RATE)
# Third, a thread that listens for transcription responses
recognize_stream = service.StreamingRecognize(
requests, DEADLINE_SECS)
# Exit things cleanly on interrupt
# signal.signal(signal.SIGINT, lambda *_: recognize_stream.cancel())
# Now, put the transcription responses to use.
try:
#listen_print_loop(recognize_stream,pub)
dump_output(recognize_stream,pub)
recognize_stream.cancel()
except face.CancellationError:
# This happens because of the interrupt handler
pass
print("end of session")
def run(self):
"""
Run speech recognition script
"""
with cloud_speech.beta_create_Speech_stub(
self.make_channel('speech.googleapis.com', 443)) as service:
# For streaming audio from the microphone, there are three threads.
# First, a thread that collects audio data as it comes in
with self.record_audio(self.RATE,
self.CHUNK) as buffered_audio_data:
# Second, a thread that sends requests with that data
requests = self.request_stream(buffered_audio_data, self.RATE)
# Third, a thread that listens for transcription responses
recognize_stream = service.StreamingRecognize(
requests, self.DEADLINE_SECS)
# Exit things cleanly on interrupt
#signal.signal(signal.SIGINT, lambda *_: recognize_stream.cancel())
# Now, put the transcription responses to use.
try:
while True:
self.listen_print_loop(recognize_stream)
print('done???')
recognize_stream.cancel()
except face.CancellationError:
# This happens because of the interrupt handler
pass
def main(input_uri, encoding, sample_rate, language_code='en-US'):
service = cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443))
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
response = service.SyncRecognize(
cloud_speech.SyncRecognizeRequest(
config=cloud_speech.RecognitionConfig(
# There are a bunch of config options you can specify. See
# https://goo.gl/KPZn97 for the full list.
encoding=encoding, # one of LINEAR16, FLAC, MULAW, AMR, AMR_WB
sample_rate=sample_rate, # the rate in hertz
# See https://g.co/cloud/speech/docs/languages for a list of
# supported languages.
language_code=language_code, # a BCP-47 language tag
),
audio=cloud_speech.RecognitionAudio(uri=input_uri, )),
DEADLINE_SECS)
# Print the recognition result alternatives and confidence scores.
for result in response.results:
print('Result:')
for alternative in result.alternatives:
print(u' ({}): {}'.format(alternative.confidence,
alternative.transcript))
def main(input_uri, encoding, sample_rate, language_code='en-US'):
service = cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443))
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
response = service.SyncRecognize(cloud_speech.SyncRecognizeRequest(
config=cloud_speech.RecognitionConfig(
# There are a bunch of config options you can specify. See
# https://goo.gl/KPZn97 for the full list.
encoding=encoding, # one of LINEAR16, FLAC, MULAW, AMR, AMR_WB
sample_rate=sample_rate, # the rate in hertz
# See https://g.co/cloud/speech/docs/languages for a list of
# supported languages.
language_code=language_code, # a BCP-47 language tag
),
audio=cloud_speech.RecognitionAudio(
uri=input_uri,
)
), DEADLINE_SECS)
# Print the recognition result alternatives and confidence scores.
for result in response.results:
print('Result:')
for alternative in result.alternatives:
print(u' ({}): {}'.format(
alternative.confidence, alternative.transcript))
def main(input_uri, encoding, sample_rate, language_code='en-US'):
channel = make_channel('speech.googleapis.com', 443)
service = cloud_speech_pb2.beta_create_Speech_stub(channel)
# The method and parameters can be inferred from the proto from which the
# grpc client lib was generated. See:
# https://github.com/googleapis/googleapis/blob/master/google/cloud/speech/v1beta1/cloud_speech.proto
operation = service.AsyncRecognize(
cloud_speech_pb2.AsyncRecognizeRequest(
config=cloud_speech_pb2.RecognitionConfig(
# There are a bunch of config options you can specify. See
# https://goo.gl/KPZn97 for the full list.
encoding=encoding, # one of LINEAR16, FLAC, MULAW, AMR, AMR_WB
sample_rate=sample_rate, # the rate in hertz
# See https://g.co/cloud/speech/docs/languages for a list of
# supported languages.
language_code=language_code, # a BCP-47 language tag
),
audio=cloud_speech_pb2.RecognitionAudio(uri=input_uri, )),
DEADLINE_SECS)
# Print the longrunning operation handle.
print(operation)
# Construct a long running operation endpoint.
service = operations_pb2.beta_create_Operations_stub(channel)
name = operation.name
while True:
# Give the server a few seconds to process.
print('Waiting for server processing...')
time.sleep(1)
operation = service.GetOperation(
operations_pb2.GetOperationRequest(name=name), DEADLINE_SECS)
if operation.error.message:
print('\nOperation error:\n{}'.format(operation.error))
if operation.done:
break
response = cloud_speech_pb2.AsyncRecognizeResponse()
operation.response.Unpack(response)
# Print the recognition result alternatives and confidence scores.
for result in response.results:
print('Result:')
for alternative in result.alternatives:
print(u' ({}): {}'.format(alternative.confidence,
alternative.transcript))
def main():
with cloud_speech.beta_create_Speech_stub(
make_channel('speech.googleapis.com', 443)) as service:
# For streaming audio from the microphone, there are three threads.
# First, a thread that collects audio data as it comes in
with record_audio(RATE, CHUNK) as buffered_audio_data:
# Second, a thread that sends requests with that data
requests = request_stream(buffered_audio_data, RATE)
# Third, a thread that listens for transcription responses
recognize_stream = service.StreamingRecognize(
requests, DEADLINE_SECS)
# Exit things cleanly on interrupt
signal.signal(signal.SIGINT, lambda *_: recognize_stream.cancel())
# Now, put the transcription responses to use.
try:
listen_print_loop(recognize_stream)
recognize_stream.cancel()
except face.CancellationError:
# This happens because of the interrupt handler
pass
def create_new_service():
channel = make_channel('speech.googleapis.com', 443)
service = cloud_speech.beta_create_Speech_stub(channel)
return service
