def listen(self):
service = cloud_speech_pb2.SpeechStub(self.make_channel('speech.googleapis.com', 443))
# 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 buff:
# Second, a thread that sends requests with that data
overlap_buffer = collections.deque(maxlen=self.SECS_OVERLAP * self.RATE / self.CHUNK)
requests = self.request_stream(self._audio_data_generator(buff, overlap_buffer), 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, buff)
# Discard this stream and create a new one.
# Note: calling .cancel() doesn't immediately raise an RpcError
# - it only raises when the iterator's next() is requested
recognize_stream.cancel()
requests = self.request_stream(self._audio_data_generator(
buff, overlap_buffer), self.RATE)
# Third, a thread that listens for transcription responses
recognize_stream = service.StreamingRecognize(
requests, self.DEADLINE_SECS)
except grpc.RpcError:
# This happens because of the interrupt handler
pass
def main(input_uri, encoding, sample_rate, language_code='en-US'):
service = cloud_speech_pb2.SpeechStub(
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_pb2.SyncRecognizeRequest(
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 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():
service = cloud_speech_pb2.SpeechStub(
make_channel('speech.googleapis.com', 443))
print("Speech2Text started")
# 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 grpc.RpcError as e:
code = e.code()
# CANCELLED is caused by the interrupt handler, which is expected.
if code is not code.CANCELLED:
raise
def handle_request_sound_transcript(req):
requestSoundTranscriptResponse = RequestSoundTranscriptResponse()
try:
resp = getAudioText()
requestSoundTranscriptResponse.utterance = resp.responses[0]
requestSoundTranscriptResponse.isGood = resp.isGood
except RuntimeError:
global googleSpeech
googleSpeech = cloud_speech_pb2.SpeechStub(
make_channel('speech.googleapis.com', 443))
requestSoundTranscriptResponse.isGood = False
return requestSoundTranscriptResponse
def main(input_uri, encoding, sample_rate, language_code='en-US'):
channel = make_channel('speech.googleapis.com', 443)
service = cloud_speech_pb2.SpeechStub(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.OperationsStub(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 sound_transcript_server():
rospy.init_node(NAME)
while (True):
try:
global googleSpeech
googleSpeech = cloud_speech_pb2.SpeechStub(
make_channel('speech.googleapis.com', 443))
serv = rospy.Service('sound_transcript_server',
RequestSoundTranscript,
handle_request_sound_transcript)
rospy.spin()
break
except RuntimeError:
pass
def main():
service = cloud_speech_pb2.SpeechStub(
make_channel('speech.googleapis.com', 443))
# 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 _make_service(self, channel):
return cloud_speech.SpeechStub(channel)