科大讯飞语音转写 API 文档连接: https://www.xfyun.cn/doc/asr/lfasr/API.html.
科大讯飞语音转写Python3的demo下载连接:http://xfyun-doc.ufile.ucloud.com.cn/1564736425808301/weblfasr_python3_demo.zip
上一篇写了用百度智能云进行音频文件转写的博客,可是那个效果啊,有点惨不忍睹,至少个人识别结果是这样。而后转而使用了一下科大讯飞的,想着科大讯飞专门作语音相关的这一块,应该会好些。语音转写的Python3的demo代码确实很不错,函数接口很简洁,本文代码都是这个demo里面的。识别准确率仍是能够的,并且不须要像百度那样整点才开始识别,很快就返回了识别结果。
若是你的录音是不止一我的,而是像电话录音那种,想把转写结果中不一样人说的话分离出来,请按照下面这样添加预处理参数(demo中默认是没有添加这儿最后两个参数的,不添加的话,默认是不进行角色分离的):
这样的话,转写结果的speaker的值就不全是0了,而是根据不一样的人对转写结果进行分离:
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操做系统:Windows
Python:3.6
可用时长: 免费用户时长5小时,且用且珍惜。
音频属性: 采样率16k或8k、位长8bits或16bits、单声道&多声道
音频格式: wav/flac/opus/m4a/mp3
音频大小: 不超过500M
音频时长: 不超过5小时,建议5分钟以上
语言种类: 中文普通话、英文
转写结果保存时长 30天。(同一通录音不须要从新上传识别,若是你已经上传识别过了,以后只须要使用api.get_result_request(taskid)的方式便可再次获取识别结果,taskid是你第一次上传录音时给你分配的任务ID,避免重复上传浪费可用时长)python
讯飞的好像不须要API_KEY,开放受权的方式和其余大厂的相似:
一、页面右上方“控制台”点击进入,登陆讯飞帐号(没有就注册一个),进入讯飞开放平台。
二、左侧导航栏上方,依次选择 语音识别->语音转写->离线语音转写识别。
三、服务申请。点击“建立应用”,“接口选择”已默认勾选完成,如无其余需求,无需勾选,完成其余资料后,点击最下方“当即建立”按钮。本身能够手动领取5小时免费试用体验包。
四、应用成功则页面显示“建立完毕”,点击”返回应用列表”, 查看新建立应用详情,在服务接口认证信息窗口就能够看到返回的AppID,SecretKey。web
# -*- coding: utf-8 -*- # # author: yanmeng2 # # 非实时转写调用demo import base64 import hashlib import hmac import json import os import time import requests lfasr_host = 'http://raasr.xfyun.cn/api' # 请求的接口名 api_prepare = '/prepare' api_upload = '/upload' api_merge = '/merge' api_get_progress = '/getProgress' api_get_result = '/getResult' # 文件分片大小10M file_piece_sice = 10485760 # ——————————————————转写可配置参数———————————————— # 参数可在官网界面(https://doc.xfyun.cn/rest_api/%E8%AF%AD%E9%9F%B3%E8%BD%AC%E5%86%99.html)查看,根据需求可自行在gene_params方法里添加修改 # 转写类型 lfasr_type = 0 # 是否开启分词 has_participle = 'false' has_seperate = 'true' # 多候选词个数 max_alternatives = 0 # 子用户标识 suid = '' class SliceIdGenerator: """slice id生成器""" def __init__(self): self.__ch = 'aaaaaaaaa`' def getNextSliceId(self): ch = self.__ch j = len(ch) - 1 while j >= 0: cj = ch[j] if cj != 'z': ch = ch[:j] + chr(ord(cj) + 1) + ch[j + 1:] break else: ch = ch[:j] + 'a' + ch[j + 1:] j = j - 1 self.__ch = ch return self.__ch class RequestApi(object): def __init__(self, appid, secret_key, upload_file_path): self.appid = appid self.secret_key = secret_key self.upload_file_path = upload_file_path # 根据不一样的apiname生成不一样的参数,本示例中未使用所有参数您可在官网(https://doc.xfyun.cn/rest_api/%E8%AF%AD%E9%9F%B3%E8%BD%AC%E5%86%99.html)查看后选择适合业务场景的进行更换 def gene_params(self, apiname, taskid=None, slice_id=None): appid = self.appid secret_key = self.secret_key upload_file_path = self.upload_file_path ts = str(int(time.time())) m2 = hashlib.md5() m2.update((appid + ts).encode('utf-8')) md5 = m2.hexdigest() md5 = bytes(md5, encoding='utf-8') # 以secret_key为key, 上面的md5为msg, 使用hashlib.sha1加密结果为signa signa = hmac.new(secret_key.encode('utf-8'), md5, hashlib.sha1).digest() signa = base64.b64encode(signa) signa = str(signa, 'utf-8') file_len = os.path.getsize(upload_file_path) file_name = os.path.basename(upload_file_path) param_dict = {} if apiname == api_prepare: # slice_num是指分片数量,若是您使用的音频都是较短音频也能够不分片,直接将slice_num指定为1便可 slice_num = int(file_len / file_piece_sice) + (0 if (file_len % file_piece_sice == 0) else 1) param_dict['app_id'] = appid param_dict['signa'] = signa param_dict['ts'] = ts param_dict['file_len'] = str(file_len) param_dict['file_name'] = file_name param_dict['slice_num'] = str(slice_num) elif apiname == api_upload: param_dict['app_id'] = appid param_dict['signa'] = signa param_dict['ts'] = ts param_dict['task_id'] = taskid param_dict['slice_id'] = slice_id elif apiname == api_merge: param_dict['app_id'] = appid param_dict['signa'] = signa param_dict['ts'] = ts param_dict['task_id'] = taskid param_dict['file_name'] = file_name elif apiname == api_get_progress or apiname == api_get_result: param_dict['app_id'] = appid param_dict['signa'] = signa param_dict['ts'] = ts param_dict['task_id'] = taskid return param_dict # 请求和结果解析,结果中各个字段的含义可参考:https://doc.xfyun.cn/rest_api/%E8%AF%AD%E9%9F%B3%E8%BD%AC%E5%86%99.html def gene_request(self, apiname, data, files=None, headers=None): response = requests.post(lfasr_host + apiname, data=data, files=files, headers=headers) result = json.loads(response.text) if result["ok"] == 0: print("{} success:".format(apiname) + str(result)) return result else: print("{} error:".format(apiname) + str(result)) exit(0) return result # 预处理 def prepare_request(self): return self.gene_request(apiname=api_prepare, data=self.gene_params(api_prepare)) # 上传 def upload_request(self, taskid, upload_file_path): file_object = open(upload_file_path, 'rb') try: index = 1 sig = SliceIdGenerator() while True: content = file_object.read(file_piece_sice) if not content or len(content) == 0: break files = { "filename": self.gene_params(api_upload).get("slice_id"), "content": content } response = self.gene_request(api_upload, data=self.gene_params(api_upload, taskid=taskid, slice_id=sig.getNextSliceId()), files=files) if response.get('ok') != 0: # 上传分片失败 print('upload slice fail, response: ' + str(response)) return False print('upload slice ' + str(index) + ' success') index += 1 finally: 'file index:' + str(file_object.tell()) file_object.close() return True # 合并 def merge_request(self, taskid): return self.gene_request(api_merge, data=self.gene_params(api_merge, taskid=taskid)) # 获取进度 def get_progress_request(self, taskid): return self.gene_request(api_get_progress, data=self.gene_params(api_get_progress, taskid=taskid)) # 获取结果 def get_result_request(self, taskid): return self.gene_request(api_get_result, data=self.gene_params(api_get_result, taskid=taskid)) def all_api_request(self): # 1. 预处理 pre_result = self.prepare_request() taskid = pre_result["data"] # 2 . 分片上传 self.upload_request(taskid=taskid, upload_file_path=self.upload_file_path) # 3 . 文件合并 self.merge_request(taskid=taskid) # 4 . 获取任务进度 while True: # 每隔20秒获取一次任务进度 progress = self.get_progress_request(taskid) progress_dic = progress if progress_dic['err_no'] != 0 and progress_dic['err_no'] != 26605: print('task error: ' + progress_dic['failed']) return else: data = progress_dic['data'] task_status = json.loads(data) if task_status['status'] == 9: print('task ' + taskid + ' finished') break print('The task ' + taskid + ' is in processing, task status: ' + str(data)) # 每次获取进度间隔20S time.sleep(20) # 5 . 获取结果 self.get_result_request(taskid=taskid) # 注意:若是出现requests模块报错:"NoneType" object has no attribute 'read', 请尝试将requests模块更新到2.20.0或以上版本(本demo测试版本为2.20.0) # 输入讯飞开放平台的appid,secret_key和待转写的文件路径 if __name__ == '__main__': APP_ID = "***" SECRET_KEY = "****" file_path = r"***.wav" api = RequestApi(appid=APP_ID, secret_key=SECRET_KEY, upload_file_path=file_path) api.all_api_request()
固然,你能够根据本身的需求对demo进行改进,好比你想并发识别录音,你能够添加多线程执行的函数,为了获取taskid方便,我在class的初始化里边添加了self.taskid = “None”,并在预处理结果返回以后从新对taskid赋值。
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def thread_func(wav_file_path, txt_file_path): # 线程函数,方便并发识别录音 doc = open(txt_file_path, 'w', encoding='utf-8') # doc.close() api = RequestApi(appid=APP_ID, secret_key=SECRET_KEY, upload_file_path=wav_file_path) api.all_api_request() # demo中这个函数是完整过程执行,但我把提取结果的模块提出来了 print('taskid is: ' + api.taskid, file=doc) result = api.get_result_request(api.taskid) result = eval(result['data']) # print(result) for x in result: print(x) print(x, file=doc) doc.close() #主函数写成相似这种 if __name__ == '__main__': file_list = [ "o2019082112552587460156", "o2019082115552587460127" ] APP_ID = "***" SECRET_KEY = "***" file_read_path = r"D:\MyProject\Python\Voice_SDK\20190820\\" file_save_path = r"D:\MyProject\Python\Voice_SDK\20190820_xunfei\\" for file in file_list: #多并发批量执行 wav_file_path = file_read_path + file + ".wav" txt_file_path = file_save_path + file + ".txt" t = threading.Thread(target=thread_func, args=(wav_file_path, txt_file_path)) t.start()