Question

我正在跟踪一个有关IBM Watson Python SDK的示例，Github发现here

我在第47行更改了以下代码

def on_transcription(self, transcript):
        print(transcript)

到

def on_transcription(self, transcript):
        print(transcript)
        data = json.loads(transcript)
        print(data[0]['transcript'])

但是，我的代码从未到达第二个打印语句。

screenshot of code output

代码在第一个打印语句之后停止，并在那里停留了很长一段时间。

我再次用

进行了测试

def on_transcription(self, transcript):
        print("1")
        data = json.loads(transcript)
        print("2")

screenshot of code output

代码再也不会到达打印语句

有人可以帮助我理解为什么代码不断卡住吗？

这是完整的代码：

# You need to install pyaudio to run this example
# pip install pyaudio

# When using a microphone, the AudioSource `input` parameter would be
# initialised as a queue. The pyaudio stream would be continuosly adding
# recordings to the queue, and the websocket client would be sending the
# recordings to the speech to text service

from __future__ import print_function
import pyaudio
from ibm_watson import SpeechToTextV1
from ibm_watson.websocket import RecognizeCallback, AudioSource
from threading import Thread

try:
    from Queue import Queue, Full
except ImportError:
    from queue import Queue, Full

###############################################
#### Initalize queue to store the recordings ##
###############################################
CHUNK = 1024
# Note: It will discard if the websocket client can't consumme fast enough
# So, increase the max size as per your choice
BUF_MAX_SIZE = CHUNK * 10
# Buffer to store audio
q = Queue(maxsize=int(round(BUF_MAX_SIZE / CHUNK)))

# Create an instance of AudioSource
audio_source = AudioSource(q, True, True)

###############################################
#### Prepare Speech to Text Service ########
###############################################

# initialize speech to text service
speech_to_text = SpeechToTextV1(
    iam_apikey='I replaced with my API key',
    url='I replaced with my URL')

# define callback for the speech to text service
class MyRecognizeCallback(RecognizeCallback):
    def __init__(self):
        RecognizeCallback.__init__(self)

    def on_transcription(self, transcript):
        print("1")
        data = json.loads(transcript)
        print("2")

    def on_connected(self):
        print('Connection was successful')

    def on_error(self, error):
        print('Error received: {}'.format(error))

    def on_inactivity_timeout(self, error):
        print('Inactivity timeout: {}'.format(error))

    def on_listening(self):
        print('Service is listening')

    #def on_hypothesis(self, hypothesis):
    #    print(hypothesis)

    #def on_data(self, data):
    #    #print(data)

    def on_close(self):
        print("Connection closed")

# this function will initiate the recognize service and pass in the AudioSource
def recognize_using_weboscket(*args):
    mycallback = MyRecognizeCallback()
    speech_to_text.recognize_using_websocket(audio=audio_source,
                                             content_type='audio/l16; rate=44100',
                                             recognize_callback=mycallback,
                                             interim_results=True)

###############################################
#### Prepare the for recording using Pyaudio ##
###############################################

# Variables for recording the speech
FORMAT = pyaudio.paInt16
CHANNELS = 1
RATE = 44100

# define callback for pyaudio to store the recording in queue
def pyaudio_callback(in_data, frame_count, time_info, status):
    try:
        q.put(in_data)
    except Full:
        pass # discard
    return (None, pyaudio.paContinue)

# instantiate pyaudio
audio = pyaudio.PyAudio()

# open stream using callback
stream = audio.open(
    format=FORMAT,
    channels=CHANNELS,
    rate=RATE,
    input=True,
    frames_per_buffer=CHUNK,
    stream_callback=pyaudio_callback,
    start=False
)

#########################################################################
#### Start the recording and start service to recognize the stream ######
#########################################################################

print("Enter CTRL+C to end recording...")
stream.start_stream()

try:
    recognize_thread = Thread(target=recognize_using_weboscket, args=())
    recognize_thread.start()

    while True:
        pass
except KeyboardInterrupt:
    # stop recording
    stream.stop_stream()
    stream.close()
    audio.terminate()
    audio_source.completed_recording()

Answer 1

您不需要“ json.loads”传递到on_transcription的脚本值-它已经被反序列化为dict。

无法解析IBM Watson Speech To Text的JSON输出

1 个答案: