speech_recognition/examples/threaded_workers.py at master · markmiao/speech_recognition

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#!/usr/bin/env python3

# NOTE: this example requires PyAudio because it uses the Microphone class

from threading import Thread

from queue import Queue

import speech_recognition as sr

r = sr.Recognizer()

audio_queue = Queue()

def recognize_worker():

# this runs in a background thread

while True:

audio = audio_queue.get() # retrieve the next audio processing job from the main thread

if audio is None: break # stop processing if the main thread is done

# received audio data, now we'll recognize it using Google Speech Recognition

try:

# for testing purposes, we're just using the default API key

# to use another API key, use `r.recognize_google(audio, key="GOOGLE_SPEECH_RECOGNITION_API_KEY")`

# instead of `r.recognize_google(audio)`

print("Google Speech Recognition thinks you said " + r.recognize_google(audio))

except sr.UnknownValueError:

print("Google Speech Recognition could not understand audio")

except sr.RequestError as e:

print("Could not request results from Google Speech Recognition service; {0}".format(e))

audio_queue.task_done() # mark the audio processing job as completed in the queue

# start a new thread to recognize audio, while this thread focuses on listening

recognize_thread = Thread(target=recognize_worker)

recognize_thread.daemon = True

recognize_thread.start()

with sr.Microphone() as source:

try:

while True: # repeatedly listen for phrases and put the resulting audio on the audio processing job queue

audio_queue.put(r.listen(source))

except KeyboardInterrupt: # allow Ctrl + C to shut down the program

pass

audio_queue.join() # block until all current audio processing jobs are done

audio_queue.put(None) # tell the recognize_thread to stop

recognize_thread.join() # wait for the recognize_thread to actually stop

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