Speech continuous [(#1940)](#1940)

* Draft 1: indefinitely-long streaming transcription

* Clean up & refactor of indefinite speech transcrib

* Make sure chunks_per_second is a whole number.

* Update for google-cloud-python client lib.

* Update sample to not error out, but make a new request every ~60ish seconds

* Update transcribe_streaming_mic.py

* Clean up unnecessary code, since we no longer wait for it to error out

* Update based on feedback

speech/snippets/requirements.txt

@@ -1 +1,3 @@
 google-cloud-speech==0.36.0
+pyaudio==0.2.11
+six==1.12.0

speech/snippets/transcribe_streaming_indefinite.py

@@ -0,0 +1,223 @@
+#!/usr/bin/env python
+
+# Copyright 2018 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.
+
+"""Google Cloud Speech API sample application using the streaming API.
+
+NOTE: This module requires the additional dependency `pyaudio`. To install
+using pip:
+
+    pip install pyaudio
+
+Example usage:
+    python transcribe_streaming_indefinite.py
+"""
+
+# [START speech_transcribe_infinite_streaming]
+from __future__ import division
+
+import time
+import re
+import sys
+
+from google.cloud import speech
+
+import pyaudio
+from six.moves import queue
+
+# Audio recording parameters
+STREAMING_LIMIT = 55000
+SAMPLE_RATE = 16000
+CHUNK_SIZE = int(SAMPLE_RATE / 10)  # 100ms
+
+
+def get_current_time():
+    return int(round(time.time() * 1000))
+
+
+def duration_to_secs(duration):
+    return duration.seconds + (duration.nanos / float(1e9))
+
+
+class ResumableMicrophoneStream:
+    """Opens a recording stream as a generator yielding the audio chunks."""
+    def __init__(self, rate, chunk_size):
+        self._rate = rate
+        self._chunk_size = chunk_size
+        self._num_channels = 1
+        self._max_replay_secs = 5
+
+        # Create a thread-safe buffer of audio data
+        self._buff = queue.Queue()
+        self.closed = True
+        self.start_time = get_current_time()
+
+        # 2 bytes in 16 bit samples
+        self._bytes_per_sample = 2 * self._num_channels
+        self._bytes_per_second = self._rate * self._bytes_per_sample
+
+        self._bytes_per_chunk = (self._chunk_size * self._bytes_per_sample)
+        self._chunks_per_second = (
+                self._bytes_per_second // self._bytes_per_chunk)
+
+    def __enter__(self):
+        self.closed = False
+
+        self._audio_interface = pyaudio.PyAudio()
+        self._audio_stream = self._audio_interface.open(
+            format=pyaudio.paInt16,
+            channels=self._num_channels,
+            rate=self._rate,
+            input=True,
+            frames_per_buffer=self._chunk_size,
+            # Run the audio stream asynchronously to fill the buffer object.
+            # This is necessary so that the input device's buffer doesn't
+            # overflow while the calling thread makes network requests, etc.
+            stream_callback=self._fill_buffer,
+        )
+
+        return self
+
+    def __exit__(self, type, value, traceback):
+        self._audio_stream.stop_stream()
+        self._audio_stream.close()
+        self.closed = True
+        # Signal the generator to terminate so that the client's
+        # streaming_recognize method will not block the process termination.
+        self._buff.put(None)
+        self._audio_interface.terminate()
+
+    def _fill_buffer(self, in_data, *args, **kwargs):
+        """Continuously collect data from the audio stream, into the buffer."""
+        self._buff.put(in_data)
+        return None, pyaudio.paContinue
+
+    def generator(self):
+        while not self.closed:
+            if get_current_time() - self.start_time > STREAMING_LIMIT:
+                self.start_time = get_current_time()
+                break
+            # Use a blocking get() to ensure there's at least one chunk of
+            # data, and stop iteration if the chunk is None, indicating the
+            # end of the audio stream.
+            chunk = self._buff.get()
+            if chunk is None:
+                return
+            data = [chunk]
+
+            # Now consume whatever other data's still buffered.
+            while True:
+                try:
+                    chunk = self._buff.get(block=False)
+                    if chunk is None:
+                        return
+                    data.append(chunk)
+                except queue.Empty:
+                    break
+
+            yield b''.join(data)
+
+
+def listen_print_loop(responses, stream):
+    """Iterates through server responses and prints them.
+
+    The responses passed is a generator that will block until a response
+    is provided by the server.
+
+    Each response may contain multiple results, and each result may contain
+    multiple alternatives; for details, see https://goo.gl/tjCPAU.  Here we
+    print only the transcription for the top alternative of the top result.
+
+    In this case, responses are provided for interim results as well. If the
+    response is an interim one, print a line feed at the end of it, to allow
+    the next result to overwrite it, until the response is a final one. For the
+    final one, print a newline to preserve the finalized transcription.
+    """
+    responses = (r for r in responses if (
+            r.results and r.results[0].alternatives))
+
+    num_chars_printed = 0
+    for response in responses:
+        if not response.results:
+            continue
+
+        # The `results` list is consecutive. For streaming, we only care about
+        # the first result being considered, since once it's `is_final`, it
+        # moves on to considering the next utterance.
+        result = response.results[0]
+        if not result.alternatives:
+            continue
+
+        # Display the transcription of the top alternative.
+        top_alternative = result.alternatives[0]
+        transcript = top_alternative.transcript
+
+        # Display interim results, but with a carriage return at the end of the
+        # line, so subsequent lines will overwrite them.
+        #
+        # If the previous result was longer than this one, we need to print
+        # some extra spaces to overwrite the previous result
+        overwrite_chars = ' ' * (num_chars_printed - len(transcript))
+
+        if not result.is_final:
+            sys.stdout.write(transcript + overwrite_chars + '\r')
+            sys.stdout.flush()
+
+            num_chars_printed = len(transcript)
+        else:
+            print(transcript + overwrite_chars)
+
+            # Exit recognition if any of the transcribed phrases could be
+            # one of our keywords.
+            if re.search(r'\b(exit|quit)\b', transcript, re.I):
+                print('Exiting..')
+                stream.closed = True
+                break
+
+            num_chars_printed = 0
+
+
+def main():
+    client = speech.SpeechClient()
+    config = speech.types.RecognitionConfig(
+        encoding=speech.enums.RecognitionConfig.AudioEncoding.LINEAR16,
+        sample_rate_hertz=SAMPLE_RATE,
+        language_code='en-US',
+        max_alternatives=1,
+        enable_word_time_offsets=True)
+    streaming_config = speech.types.StreamingRecognitionConfig(
+        config=config,
+        interim_results=True)
+
+    mic_manager = ResumableMicrophoneStream(SAMPLE_RATE, CHUNK_SIZE)
+
+    print('Say "Quit" or "Exit" to terminate the program.')
+
+    with mic_manager as stream:
+        while not stream.closed:
+            audio_generator = stream.generator()
+            requests = (speech.types.StreamingRecognizeRequest(
+                audio_content=content)
+                for content in audio_generator)
+
+            responses = client.streaming_recognize(streaming_config,
+                                                   requests)
+            # Now, put the transcription responses to use.
+            listen_print_loop(responses, stream)
+
+
+if __name__ == '__main__':
+    main()
+# [END speech_transcribe_infinite_streaming]