Python结合百度语音识别实现实时翻译软件的实现

一、所需库安装

pip install PyAudio
pip install SpeechRecognition
pip install baidu-aip
pip install Wave
pip install Wheel
pip install Pyinstaller

二、百度官网申请服务

三、源代码分享

import pyaudio
import wave
from aip import AipSpeech
import time




# 用Pyaudio库录制音频
#  out_file:输出音频文件名
#  rec_time:音频录制时间(秒)
def audio_record(out_file, rec_time):
  CHUNK = 1024
  FORMAT = pyaudio.paInt16 # 16bit编码格式
  CHANNELS = 1 # 单声道
  RATE = 16000 # 16000采样频率

  p = pyaudio.PyAudio()
  # 创建音频流
  stream = p.open(format=FORMAT, # 音频流wav格式
          channels=CHANNELS, # 单声道
          rate=RATE, # 采样率16000
          input=True,
          frames_per_buffer=CHUNK)

  print(\"开始记录语音{0}秒后开始识别...\".format(rec_time))

  frames = [] # 录制的音频流
  # 录制音频数据
  for i in range(0, int(RATE / CHUNK * rec_time)):
    data = stream.read(CHUNK)
    frames.append(data)

  # 录制完成
  stream.stop_stream()
  stream.close()
  p.terminate()

  print(\"结束识别\")

  # 保存音频文件
  wf = wave.open(out_file, \'wb\')
  wf.setnchannels(CHANNELS)
  wf.setsampwidth(p.get_sample_size(FORMAT))
  wf.setframerate(RATE)
  wf.writeframes(b\'\'.join(frames))
  wf.close()


def audio_recog(recogFile):
  # 读取文件
  def get_file_content(filePath):
    with open(filePath, \'rb\') as fp:
      return fp.read()


  # 识别本地文件
  result = client.asr(get_file_content(recogFile), \'wav\', 16000, {\'dev_pid\': 1537,})
  return result

def write_file(file,text):
  import time
  time = time.strftime(\"%Y-%m-%d %H:%M:%S\", time.localtime())
  f = open(file, \'a\')
  f.write(time+\':\'+text+\'\\n\')
  f.close()

audioFile=\"audio.wav\"
textFile=\"识别结果.txt\"

\"\"\" 你的 APPID AK SK \"\"\"
APP_ID = \'你的APP_ID\'
API_KEY = \'你的API_KEY\'
SECRET_KEY = \'你的SECRET_KEY\'

client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)


if __name__ == \'__main__\':
  while True:
    audio_record(audioFile, 5)
    textResult = audio_recog(\"audio.wav\")
    if textResult[\'err_msg\'] ==\"success.\":
      print(textResult[\'result\'])
      write_file(textFile,str(textResult[\'result\']))