（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：
#!/usr/bin/python3import urllib.requestimport urllibimport jsonimport base64class 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：#!/usr/bin/python3# -*- coding: utf-8 -*-from pyaudio import PyAudio, paInt16 import numpy as np from datetime import datetime import waveclass 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 Falseif __name__ == "__main__": r = recoder() r.recoder() r.savewav("test.wav")