python调用百度语音REST API_Python

本文实例为大家分享了python调用百度语音REST API的具体代码，供大家参考，具体内容如下

（百度的rest接口的部分网址发生了一定的变化，相关代码已更新）

百度通过 REST API 的方式给开发者提供一个通用的 HTTP 接口，基于该接口，开发者可以轻松的获得语音合成与语音识别能力。SDK中只提供了PHP、C和JAVA的相关样例，使用python也可以灵活的对端口进行调用，本文描述了简单使用Python调用百度语音识别服务 REST API 的简单样例。

1、语音识别与语音合成的调用

注册开发者帐号和创建应用的过程就不再赘述，百度的REST API在调用过程基本分为三步：

获取token
向Rest接口提交数据
处理返回数据

具体代码如下所示：

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									#!/usr/bin/python3

									import urllib.request

									import urllib

									import json

									import base64

									class BaiduRest:

									  def __init__(self, cu_id, api_key, api_secert):

									    # token认证的url

									    self.token_url = "https://openapi.baidu.com/oauth/2.0/token?grant_type=client_credentials&client_id=%s&client_secret=%s"

									    # 语音合成的resturl

									    self.getvoice_url = "http://tsn.baidu.com/text2audio?tex=%s&lan=zh&cuid=%s&ctp=1&tok=%s"

									    # 语音识别的resturl

									    self.upvoice_url = 'http://vop.baidu.com/server_api'

									    self.cu_id = cu_id

									    self.getToken(api_key, api_secert)

									    return

									  def getToken(self, api_key, api_secert):

									    # 1.获取token

									    token_url = self.token_url % (api_key,api_secert)

									    r_str = urllib.request.urlopen(token_url).read()

									    token_data = json.loads(r_str)

									    self.token_str = token_data['access_token']

									    pass

									  def getVoice(self, text, filename):

									    # 2. 向Rest接口提交数据

									    get_url = self.getvoice_url % (urllib.parse.quote(text), self.cu_id, self.token_str)

									    voice_data = urllib.request.urlopen(get_url).read()

									    # 3.处理返回数据

									    voice_fp = open(filename,'wb+')

									    voice_fp.write(voice_data)

									    voice_fp.close()

									    pass

									  def getText(self, filename):

									    # 2. 向Rest接口提交数据

									    data = {}

									    # 语音的一些参数

									    data['format'] = 'wav'

									    data['rate'] = 8000

									    data['channel'] = 1

									    data['cuid'] = self.cu_id

									    data['token'] = self.token_str

									    wav_fp = open(filename,'rb')

									    voice_data = wav_fp.read()

									    data['len'] = len(voice_data)

									    data['speech'] = base64.b64encode(voice_data).decode('utf-8')

									    post_data = json.dumps(data)

									    r_data = urllib.request.urlopen(self.upvoice_url,data=bytes(post_data,encoding="utf-8")).read()

									    # 3.处理返回数据

									    return json.loads(r_data)['result']

									if __name__ == "__main__":

									  # 我的api_key,供大家测试用，在实际工程中请换成自己申请的应用的key和secert

									  api_key = "SrhYKqzl3SE1URnAEuZ0FKdT"

									  api_secert = "hGqeCkaMPb0ELMqtRGc2VjWdmjo7T89d"

									  # 初始化

									  bdr = BaiduRest("test_python", api_key, api_secert)

									  # 将字符串语音合成并保存为out.mp3

									  bdr.getVoice("你好北京邮电大学!", "out.mp3")

									  # 识别test.wav语音内容并显示

									  print(bdr.getText("out.wav"))

2、调用pyaudio使用麦克风录制声音

python中的pyaudio库可以直接通过麦克风录制声音，可使用pip进行安装。我们可以通过调用该库，获取到wav测试语音。
具体代码如下所示：

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									#!/usr/bin/python3

									# -*- coding: utf-8 -*-

									from pyaudio import PyAudio, paInt16 

									import numpy as np 

									from datetime import datetime 

									import wave

									class recoder:

									  NUM_SAMPLES = 2000   #pyaudio内置缓冲大小

									  SAMPLING_RATE = 8000  #取样频率

									  LEVEL = 500     #声音保存的阈值

									  COUNT_NUM = 20   #NUM_SAMPLES个取样之内出现COUNT_NUM个大于LEVEL的取样则记录声音

									  SAVE_LENGTH = 8     #声音记录的最小长度：SAVE_LENGTH * NUM_SAMPLES 个取样

									  TIME_COUNT = 60   #录音时间，单位s

									  Voice_String = []

									  def savewav(self,filename):

									    wf = wave.open(filename, 'wb') 

									    wf.setnchannels(1) 

									    wf.setsampwidth(2) 

									    wf.setframerate(self.SAMPLING_RATE) 

									    wf.writeframes(np.array(self.Voice_String).tostring()) 

									    # wf.writeframes(self.Voice_String.decode())

									    wf.close() 

									  def recoder(self):

									    pa = PyAudio() 

									    stream = pa.open(format=paInt16, channels=1, rate=self.SAMPLING_RATE, input=True, 

									      frames_per_buffer=self.NUM_SAMPLES) 

									    save_count = 0

									    save_buffer = [] 

									    time_count = self.TIME_COUNT

									    while True:

									      time_count -= 1

									      # print time_count

									      # 读入NUM_SAMPLES个取样

									      string_audio_data = stream.read(self.NUM_SAMPLES) 

									      # 将读入的数据转换为数组

									      audio_data = np.fromstring(string_audio_data, dtype=np.short)

									      # 计算大于LEVEL的取样的个数

									      large_sample_count = np.sum( audio_data > self.LEVEL )

									      print(np.max(audio_data))

									      # 如果个数大于COUNT_NUM，则至少保存SAVE_LENGTH个块

									      if large_sample_count > self.COUNT_NUM:

									        save_count = self.SAVE_LENGTH 

									      else: 

									        save_count -= 1

									      if save_count < 0:

									        save_count = 0

									      if save_count > 0 : 

									      # 将要保存的数据存放到save_buffer中

									        #print save_count > 0 and time_count >0

									        save_buffer.append( string_audio_data ) 

									      else: 

									      #print save_buffer

									      # 将save_buffer中的数据写入WAV文件，WAV文件的文件名是保存的时刻

									        #print "debug"

									        if len(save_buffer) > 0 : 

									          self.Voice_String = save_buffer

									          save_buffer = [] 

									          print("Recode a piece of voice successfully!")

									          return True

									      if time_count==0: 

									        if len(save_buffer)>0:

									          self.Voice_String = save_buffer

									          save_buffer = [] 

									          print("Recode a piece of voice successfully!")

									          return True

									        else:

									          return False

									if __name__ == "__main__":

									  r = recoder()

									  r.recoder()

									  r.savewav("test.wav")