本文为大家分享了python实现大音频文件语音识别功能的具体代码，供大家参考，具体内容如下

实现思路：先用ffmpeg将其他非wav格式的音频转换为wav格式，并转换音频的声道（百度支持声道为1），采样率（值为8000），格式转换完成后，再用ffmpeg将音频切成百度。

支持的时长（30秒和60秒2种，本程序用的是30秒）。

# coding: utf-8import jsonimport timeimport base64from inc import rtysdbimport urllib2import requestsimport osimport uuidfrom inc import db_config class BaiduRest: def __init__(self, cu_id, api_key, api_secert): self.token_url = "https://openapi.baidu.com/oauth/2.0/token?grant_type=client_credentials&client_id=%s&client_secret=%s" self.getvoice_url = "http://tsn.baidu.com/text2audio?tex=%s&lan=zh&cuid=%s&ctp=1&tok=%s" self.upvoice_url = 'http://vop.baidu.com/server_api' self.cu_id = cu_id self.get_token(api_key, api_secert) return def get_token(self, api_key, api_secert): token_url = self.token_url % (api_key, api_secert) r_str = urllib2.urlopen(token_url).read() token_data = json.loads(r_str) self.token_str = token_data['access_token'] return True # 语音合成 def text2audio(self, text, filename): get_url = self.getvoice_url % (urllib2.quote(text), self.cu_id, self.token_str) voice_data = urllib2.urlopen(get_url).read() voice_fp = open(filename, 'wb+') voice_fp.write(voice_data) voice_fp.close() return True ##语音识别 def audio2text(self, filename): data = {} 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') data['speech'] = base64.b64encode(voice_data).replace('\n', '') # post_data = json.dumps(data) result = requests.post(self.upvoice_url, json=data, headers={'Content-Type': 'application/json'}) data_result = result.json() if(data_result['err_msg'] == 'success.'): return data_result['result'][0] else: return False def test_voice(voice_file): api_key = "vossGHIgEETS6IMRxBDeahv8" api_secert = "3c1fe6a6312f41fa21fa2c394dad5510" bdr = BaiduRest("0-57-7B-9F-1F-A1", api_key, api_secert) # 生成 #start = time.time() #bdr.text2audio("你好啊", "out.wav") #using = time.time() - start #print using # 识别 #start = time.time() result = bdr.audio2text(voice_file) # result = bdr.audio2text("weather.pcm") #using = time.time() - start return result def get_master_audio(check_status='cut_status'): if check_status == 'cut_status': sql = "SELECT id,url, time_long,sharps FROM ocenter_recognition WHERE status=0" elif check_status == 'finished_status': sql = "SELECT id,url, time_long,sharps FROM ocenter_recognition WHERE finished_status=0" else: return False data = rtysdb.select_data(sql,'more') if data: return data else: return False def go_recognize(master_id): section_path = db_config.SYS_PATH sql = "SELECT id,rid,url,status FROM ocenter_section WHERE rid=%d AND status=0 order by id asc limit 10" % (master_id) #print sql record = rtysdb.select_data(sql,'more') #print record if not record: return False for rec in record: #print section_path+'/'+rec[1] voice_file = section_path+'/'+rec[2] if not os.path.exists(voice_file): continue result = test_voice(voice_file) print result exit(0) if result: #rtysdb.update_by_pk('ocenter_section',rec[0],{'content':result,'status':1}) sql = "update ocenter_section set content='%s', status='%d' where id=%d" % (result,1,rec[0]) #print sql rtysdb.do_exec_sql(sql) parent_content = rtysdb.select_data("SELECT id,content FROM ocenter_recognition WHERE id=%d" % (rec[1])) #print parent_content if parent_content: new_content = parent_content[1]+result update_content_sql = "update ocenter_recognition set content='%s' where id=%d" % (new_content,rec[1]) rtysdb.do_exec_sql(update_content_sql) else: rtysdb.do_exec_sql("update ocenter_section set status='%d' where id=%d" % (result,1,rec[0])) time.sleep(5) else: rtysdb.do_exec_sql("UPDATE ocenter_recognition SET finished_status=1 WHERE id=%d" % (master_id))#对百度语音识别不了的音频文件进行转换def ffmpeg_convert(): section_path = db_config.SYS_PATH #print section_path used_audio = get_master_audio('cut_status') #print used_audio if used_audio: for audio in used_audio: audio_path = section_path+'/'+audio[1] new_audio = uuid.uuid1() command_line = "ffmpeg -i "+audio_path +" -ar 8000 -ac 1 -f wav "+section_path+"/Uploads/Convert/convert_" + str(new_audio) +".wav"; #print command_line os.popen(command_line) if os.path.exists(section_path+"/Uploads/Convert/convert_" + str(new_audio) +".wav"): convert_name = "Uploads/Convert/convert_" + str(new_audio) +".wav" ffmpeg_cut(convert_name,audio[3],audio[0]) sql = "UPDATE ocenter_recognition SET status=1,convert_name='%s' where id=%d" % (convert_name,audio[0]) rtysdb.do_exec_sql(sql)#将大音频文件切成碎片def ffmpeg_cut(convert_name,sharps,master_id): section_path = db_config.SYS_PATH if sharps>0: for i in range(0,sharps): timeArray = time.localtime(i*30) h = time.strftime("%H", timeArray) h = int(h) - 8 h = "0" + str(h) ms = time.strftime("%M:%S",timeArray) start_time = h+':'+str(ms) cut_name = section_path+'/'+convert_name db_store_name = "Uploads/Section/"+str(uuid.uuid1())+'-'+str(i+1)+".wav" section_name = section_path+"/"+db_store_name command_line = "ffmpeg.exe -i "+cut_name+" -vn -acodec copy -ss "+start_time+" -t 00:00:30 "+section_name #print command_line os.popen(command_line) data = {} data['rid'] = master_id data['url'] = db_store_name data['create_time'] = int(time.time()) data['status'] = 0 rtysdb.insert_one('ocenter_section',data) if __name__ == "__main__": ffmpeg_convert() audio = get_master_audio('finished_status') if audio: for ad in audio: go_recognize(ad[0])

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持。