test100.zip.zip

基本上，我所看到的是当我将麦克风作为信号源运行时，它仅每隔几秒钟循环一次while循环，如“。”所示。打印出来。

如果将源更改为音频文件（我包括一个小文件），则确实会循环播放整个BUNCH，如滚动“'”所示。打印到终端。它确实处理了音频（我发现很奇怪），但是被它吹了。

如果您按下CTRL C，它将最终停止，但是它与文件处理后让它运行多长时间完全相同。

还有一个奇怪的是，我创建了一个函数来将在每个循环中生成的音频数据实例保存到wav文件中，并且它们都是44字节（仅在几秒钟的执行时间内就超过了200个字节。但是，当我这样做时）从麦克风采样的音频也是如此，它可以按预期工作，并且仅生成10秒的文件。

代码如下。谢谢大家的时间。

import speech_recognition as sr
from threading import Thread
try:
    from queue import Queue  # Python 3 import
except ImportError:
    from Queue import Queue  # Python 2 import

audio_queue = Queue()
r = sr.Recognizer()

def audio_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))    

            incoming = r.recognize_google(audio)
            franzWordLizst = incoming.split()

            print("Google Speech Recognition thinks you said " + incoming)

        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))

        print("taskdone")
        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
audio_thread = Thread(target=audio_worker)


audio_thread.daemon = True


audio_thread.start()

# with sr.AudioFile("test100.wav") as source:

with sr.microphone(0) as source:
    # r.adjust_for_ambient_noise(source)
    try:
        while True:  # repeatedly listen for phrases and put the resulting audio on the audio processing job queue
            print(".")
            audio_queue.put(r.listen(source,phrase_time_limit=10))
    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