feat(speech): Add Speech-to-Text On-Prem sample

speech/cloud-client/transcribe_onprem.py

@@ -0,0 +1,91 @@
+#!/usr/bin/env python
+
+# Copyright 2020, Google LLC
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import argparse
+
+
+# [START speech_transcribe_onprem]
+def transcribe_onprem(local_file_path, api_endpoint):
+    """
+    Transcribe a short audio file using synchronous speech recognition on-prem
+
+    Args:
+      local_file_path: The path to local audio file, e.g. /path/audio.wav
+      api_endpoint: Endpoint to call for speech recognition, e.g. 0.0.0.0:10000
+    """
+    from google.cloud import speech_v1p1beta1
+    from google.cloud.speech_v1p1beta1 import enums
+    import grpc
+    import io
+
+    # api_endpoint = '0.0.0.0:10000'
+    # local_file_path = 'resources/brooklyn_bridge.raw'
+
+    # Set the API endpoint to direct requests to
+    client_options = {"api_endpoint": api_endpoint}
+
+    # Create a gRPC channel to your server
+    channel = grpc.insecure_channel(target=api_endpoint)
+
+    client = speech_v1p1beta1.SpeechClient(
+        client_options=client_options, channel=channel
+    )
+
+    # The language of the supplied audio
+    language_code = "en-US"
+
+    # Sample rate in Hertz of the audio data sent
+    sample_rate_hertz = 8000
+
+    # Encoding of audio data sent. This sample sets this explicitly.
+    # This field is optional for FLAC and WAV audio formats.
+    encoding = enums.RecognitionConfig.AudioEncoding.LINEAR16
+    config = {
+        "encoding": encoding,
+        "language_code": language_code,
+        "sample_rate_hertz": sample_rate_hertz,
+    }
+    with io.open(local_file_path, "rb") as f:
+        content = f.read()
+    audio = {"content": content}
+
+    response = client.recognize(config, audio)
+    for result in response.results:
+        # First alternative is the most probable result
+        alternative = result.alternatives[0]
+        print(u"Transcript: {}".format(alternative.transcript))
+# [END speech_transcribe_onprem]
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description=__doc__,
+        formatter_class=argparse.RawDescriptionHelpFormatter
+    )
+    parser.add_argument(
+        "--file_path",
+        required=True,
+        help="Path to local audio file to be recognized, e.g. /path/audio.wav",
+    )
+    parser.add_argument(
+        "--api_endpoint",
+        required=True,
+        help="Endpoint to call for speech recognition, e.g. 0.0.0.0:10000",
+    )
+
+    args = parser.parse_args()
+    transcribe_onprem(
+        local_file_path=args.file_path, api_endpoint=args.api_endpoint
+    )