Use pyaudio's built-in async api.

speech/grpc/transcribe_streaming.py

@@ -17,10 +17,10 @@
 from __future__ import division
 
 import contextlib
+import functools
 import re
 import signal
 import sys
-import threading
 
 from google.cloud import credentials
 from google.cloud.speech.v1beta1 import cloud_speech_pb2 as cloud_speech
@@ -76,8 +76,7 @@ def _audio_data_generator(buff):
     stop = False
     while not stop:
         # Use a blocking get() to ensure there's at least one chunk of data.
-        chunk = buff.get()
-        data = [chunk]
+        data = [buff.get()]
 
         # Now consume whatever other data's still buffered.
         while True:
@@ -86,54 +85,47 @@ def _audio_data_generator(buff):
             except queue.Empty:
                 break
 
-        # If `_fill_buffer` adds `None` to the buffer, the audio stream is
-        # closed. Yield the final bit of the buffer and exit the loop.
+        # `None` in the buffer signals that the audio stream is closed. Yield
+        # the final bit of the buffer and exit the loop.
         if None in data:
             stop = True
             data.remove(None)
+
         yield b''.join(data)
 
 
-def _fill_buffer(audio_stream, buff, chunk, stoprequest):
+def _fill_buffer(buff, in_data, frame_count, time_info, status_flags):
     """Continuously collect data from the audio stream, into the buffer."""
-    try:
-        while not stoprequest.is_set():
-            buff.put(audio_stream.read(chunk))
-    except IOError:
-        pass
-    finally:
-        # Add `None` to the buff, indicating that a stop request is made.
-        # This will signal `_audio_data_generator` to exit.
-        buff.put(None)
+    buff.put(in_data)
+    return None, pyaudio.paContinue
 
 
 # [START audio_stream]
 @contextlib.contextmanager
-def record_audio(rate, chunk, stoprequest):
+def record_audio(rate, chunk):
     """Opens a recording stream in a context manager."""
+    # Create a thread-safe buffer of audio data
+    buff = queue.Queue()
+
     audio_interface = pyaudio.PyAudio()
     audio_stream = audio_interface.open(
         format=pyaudio.paInt16,
         # The API currently only supports 1-channel (mono) audio
         # https://goo.gl/z757pE
         channels=1, rate=rate,
         input=True, frames_per_buffer=chunk,
+        # 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=functools.partial(_fill_buffer, buff),
     )
 
-    # Create a thread-safe buffer of audio data
-    buff = queue.Queue()
-
-    # Spin up a separate thread to buffer audio data from the microphone
-    # This is necessary so that the input device's buffer doesn't overflow
-    # while the calling thread makes network requests, etc.
-    fill_buffer_thread = threading.Thread(
-        target=_fill_buffer, args=(audio_stream, buff, chunk, stoprequest))
-    fill_buffer_thread.start()
-
     yield _audio_data_generator(buff)
 
-    fill_buffer_thread.join()
+    audio_stream.stop_stream()
     audio_stream.close()
+    # Signal the _audio_data_generator to finish
+    buff.put(None)
     audio_interface.terminate()
 # [END audio_stream]
 
@@ -172,7 +164,17 @@ def request_stream(data_stream, rate, interim_results=True):
         yield cloud_speech.StreamingRecognizeRequest(audio_content=data)
 
 
-def listen_print_loop(recognize_stream, stoprequest):
+def listen_print_loop(recognize_stream):
+    """Iterates through server responses and prints them.
+
+    The recognize_stream passed is a generator that will block until a response
+    is provided by the server. When the transcription response comes, print it.
+
+    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.
+    """
     num_chars_printed = 0
     for resp in recognize_stream:
         if resp.error.code != code_pb2.OK:
@@ -204,7 +206,6 @@ def listen_print_loop(recognize_stream, stoprequest):
             # one of our keywords.
             if re.search(r'\b(exit|quit)\b', transcript, re.I):
                 print('Exiting..')
-                stoprequest.set()
                 break
 
             num_chars_printed = 0
@@ -213,17 +214,9 @@ def listen_print_loop(recognize_stream, stoprequest):
 def main():
     with cloud_speech.beta_create_Speech_stub(
             make_channel('speech.googleapis.com', 443)) as service:
-
-        # stoprequest is event object which is set in `listen_print_loop`
-        # to indicate that the trancsription should be stopped.
-        #
-        # The `_fill_buffer` thread checks this object, and closes
-        # the `audio_stream` once it's set.
-        stoprequest = threading.Event()
-
         # 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, stoprequest) as buffered_audio_data:
+        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
@@ -235,7 +228,7 @@ def main():
 
             # Now, put the transcription responses to use.
             try:
-                listen_print_loop(recognize_stream, stoprequest)
+                listen_print_loop(recognize_stream)
 
                 recognize_stream.cancel()
             except face.CancellationError:

speech/grpc/transcribe_streaming_test.py

@@ -12,6 +12,7 @@
 # limitations under the License.
 
 import re
+import threading
 import time
 
 import transcribe_streaming
@@ -24,34 +25,34 @@ def __init__(self, audio_filename):
     def __call__(self, *args):
         return self
 
-    def open(self, *args, **kwargs):
-        self.audio_file = open(self.audio_filename, 'rb')
+    def open(self, stream_callback, *args, **kwargs):
+        self.closed = threading.Event()
+        self.stream_thread = threading.Thread(
+            target=self.stream_audio, args=(
+                self.audio_filename, stream_callback, self.closed))
+        self.stream_thread.start()
         return self
 
     def close(self):
-        self.audio_file.close()
+        self.closed.set()
 
     def stop_stream(self):
         pass
 
     def terminate(self):
         pass
 
-    def read(self, num_frames):
-        if self.audio_file.closed:
-            raise IOError()
-        # Approximate realtime by sleeping for the appropriate time for the
-        # requested number of frames
-        time.sleep(num_frames / float(transcribe_streaming.RATE))
-        # audio is 16-bit samples, whereas python byte is 8-bit
-        num_bytes = 2 * num_frames
-        try:
-            chunk = self.audio_file.read(num_bytes)
-        except ValueError:
-            raise IOError()
-        if not chunk:
-            raise IOError()
-        return chunk
+    @staticmethod
+    def stream_audio(audio_filename, callback, closed, num_frames=512):
+        with open(audio_filename, 'rb') as audio_file:
+            while not closed.is_set():
+                # Approximate realtime by sleeping for the appropriate time for
+                # the requested number of frames
+                time.sleep(num_frames / float(transcribe_streaming.RATE))
+                # audio is 16-bit samples, whereas python byte is 8-bit
+                num_bytes = 2 * num_frames
+                chunk = audio_file.read(num_bytes) or b'\0' * num_bytes
+                callback(chunk, None, None, None)
 
 
 def test_main(resource, monkeypatch, capsys):