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我已经使用 houndify STT 从 .wave 文件转换了 Speech-To-Text ，但是我在将文本保存到文件时遇到了问题。如何将最终流式传输的部分转录文本保存到 python 中的文件中！

 /usr/bin/env python   
 import wave  
 import houndify  
 import sys  
 import time     
 if __name__ == '__main__':  
 BUFFER_SIZE = 512   

  if len(sys.argv) < 4:  
  print "Usage: %s <client ID> <client key> <wav file> [ <more wav files> ]" % sys.argv[0]  
  sys.exit(0)

CLIENT_ID = sys.argv[1]  
CLIENT_KEY = sys.argv[2]  
class MyListener(houndify.HoundListener):  
def onPartialTranscript(self, transcript):  
  print "Partial transcript: " + transcript  
def onFinalResponse(self, response):  
  print "Final response: " + str(response)  
def onError(self, err):  
  print "Error: " + str(err)  

client = houndify.StreamingHoundClient(CLIENT_ID, CLIENT_KEY, "test_user")  
# clientMatches = [ {
 #   "Expression" : '([1/100 ("can"|"could"|"will"|"would")."you"].[1/10 "please"].("turn"|"switch"|(1/100 "flip"))."on".["the"].("light"|"lights").[1/20 "for"."me"].[1/20 "please"])|([1/100 ("can"|"could"|"will"|"would")."you"].[1/10 "please"].[100 ("turn"|"switch"|(1/100 "flip"))].["the"].("light"|"lights")."on".[1/20 "for"."me"].[1/20 "please"])|((("i".("want"|"like"))|((("i".["would"])|("i\'d")).("like"|"want"))).["the"].("light"|"lights").["turned"|"switched"|("to"."go")|(1/100"flipped")]."on".[1/20"please"])"',
 #   "Result" : { "Intent" : "TURN_LIGHT_ON" },  


for fname in sys.argv[3:]:  
print "============== %s ===================" % fname  
audio = wave.open(fname)    
if audio.getsampwidth() != 2:  
  print "%s: wrong sample width (must be 16-bit)" % fname  
  break  
if audio.getframerate() != 8000 and audio.getframerate() != 16000:  
  print "%s: unsupported sampling frequency (must be either 8 or 16 khz)" % fname  
  break  
if audio.getnchannels() != 1:  
  print "%s: must be single channel (mono)" % fname  
  break  

client.setSampleRate(audio.getframerate())  
samples = audio.readframes(BUFFER_SIZE)  
finished = False  

client.start(MyListener())  
while not finished:  
  finished = client.fill(samples)  
  time.sleep(0.032)   
  samples = audio.readframes(BUFFER_SIZE)  
  if len(samples) == 0:  
    break  
client.finish()
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