Exemplo n.º 1
0
 def _process(self, input_file, language_code):
     if not input_file.endswith('.flac'):
         raise RuntimeError('Only flac encoding file is supported.')
     audio_content = cloud_speech.RecognitionAudio(content=open(
         input_file, 'rb').read(), )
     sample_rate = self._sample_rate(input_file)
     operation = self.service.AsyncRecognize(
         cloud_speech.AsyncRecognizeRequest(
             config=cloud_speech.RecognitionConfig(
                 encoding=AUDIO_ENCODING,
                 sample_rate=sample_rate,
                 language_code=language_code,
             ),
             audio=audio_content), DEADLINE_SECS)
     return operation
Exemplo n.º 2
0
def main(input_uri, encoding, sample_rate):
    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
    response = 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/best-practices#language_support
            # for a list of supported languages.
            language_code='fi-FI',  # a BCP-47 language tag
        ),
        audio=cloud_speech_pb2.RecognitionAudio(
            uri=input_uri,
        )
    ), DEADLINE_SECS)

    # Print the longrunning operation handle.
    print >> sys.stderr, response

    # Construct a long running operation endpoint.
    service = operations_grpc_pb2.beta_create_Operations_stub(channel)

    name = response.name

    while True:
        # Give the server a few seconds to process.
        print >> sys.stderr, 'Waiting for server processing...'
        time.sleep(1)
        # Get the long running operation with response.
        response = service.GetOperation(
            operations_grpc_pb2.GetOperationRequest(name=name),
            DEADLINE_SECS)

        if response.done:
            break

    # Print the recognition results.
    results = cloud_speech_pb2.AsyncRecognizeResponse()
    response.response.Unpack(results)
    for result in results.results:
	for alternative in result.alternatives:
            print(('"{}",{}').format(alternative.transcript.encode('utf-8'), alternative.confidence))
Exemplo n.º 3
0
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_grpc_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_grpc_pb2.GetOperationRequest(name=name), DEADLINE_SECS)

        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(input_uri, encoding, sample_rate):
    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
    response = service.AsyncRecognize(
        cloud_speech_pb2.AsyncRecognizeRequest(
            config=cloud_speech_pb2.RecognitionConfig(
                encoding=encoding,
                sample_rate=sample_rate,
            ),
            audio=cloud_speech_pb2.RecognitionAudio(uri=input_uri, )),
        DEADLINE_SECS)

    # Print the longrunning operation handle.
    print(response)

    # Construct a long running operation endpoint.
    service = operations_grpc_pb2.beta_create_Operations_stub(channel)

    name = response.name

    while True:
        # Give the server a few seconds to process.
        print('Waiting for server processing...')
        time.sleep(1)
        # Get the long running operation with response.
        response = service.GetOperation(
            operations_grpc_pb2.GetOperationRequest(name=name), DEADLINE_SECS)

        if response.done:
            break

    # Print the recognition results.
    results = cloud_speech_pb2.AsyncRecognizeResponse()
    response.response.Unpack(results)
    print(results)