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-8

import json

import time

import base64

from inc import rtysdb

import urllib2

import requests

import os

import uuid

from 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脚本之家。