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#!/usr/bin/env python | |
# Copyright 2017 Google Inc. All Rights Reserved. | |
# | |
# 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_mic.py | |
--- | |
Keewon added input device selection logic. | |
Run following command before running this script | |
export GOOGLE_APPLICATION_CREDENTIALS=your_google_api_credential.json | |
""" | |
# [START speech_transcribe_streaming_mic] | |
from __future__ import division | |
import re | |
import sys | |
from google.cloud import speech | |
import pyaudio | |
from six.moves import queue | |
# Audio recording parameters | |
RATE = 16000 | |
CHUNK = int(RATE / 10) # 100ms | |
INPUT_DEVICE_NAME = 'Soundflower (2ch)' | |
INPUT_DEVICE_INDEX = None # 6 | |
class MicrophoneStream(object): | |
"""Opens a recording stream as a generator yielding the audio chunks.""" | |
def __init__(self, rate, chunk): | |
self._rate = rate | |
self._chunk = chunk | |
# Create a thread-safe buffer of audio data | |
self._buff = queue.Queue() | |
self.closed = True | |
def __enter__(self): | |
p = pyaudio.PyAudio() | |
self._audio_interface = p | |
input_device_index = None | |
for i in range(p.get_device_count()): | |
device_info = p.get_device_info_by_index(i) | |
if device_info['name'] == INPUT_DEVICE_NAME or i == INPUT_DEVICE_INDEX: | |
input_device_index = i | |
self._audio_stream = self._audio_interface.open( | |
format=pyaudio.paInt16, | |
# The API currently only supports 1-channel (mono) audio | |
# https://goo.gl/z757pE | |
channels=1, | |
rate=self._rate, | |
input=True, | |
input_device_index=input_device_index, | |
frames_per_buffer=self._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=self._fill_buffer, | |
) | |
self.closed = False | |
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, frame_count, time_info, status_flags): | |
"""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: | |
# 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): | |
"""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. | |
""" | |
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. | |
transcript = result.alternatives[0].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..") | |
break | |
num_chars_printed = 0 | |
def main(): | |
# See http://g.co/cloud/speech/docs/languages | |
# for a list of supported languages. | |
language_code = "en-US" # a BCP-47 language tag | |
client = speech.SpeechClient() | |
config = speech.RecognitionConfig( | |
encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16, | |
sample_rate_hertz=RATE, | |
language_code=language_code, | |
) | |
streaming_config = speech.StreamingRecognitionConfig( | |
config=config, interim_results=True | |
) | |
with MicrophoneStream(RATE, CHUNK) as stream: | |
audio_generator = stream.generator() | |
requests = ( | |
speech.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) | |
if __name__ == "__main__": | |
main() | |
# [END speech_transcribe_streaming_mic] | |
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