转自：https://blog.csdn.net/wolfblood_zzx/article/details/46418635

（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：

1. 获取token
2. 向Rest接口提交数据
3. 处理返回数据

具体代码如下所示：

#!/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！恭喜你的比原链又涨了!", "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：

#!/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")