【语音识别】使用短语音识别接口识别长音频文件
vincent_yan186 发布于2021-11 浏览:4150 回复:2
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一、背景:

当有音频文件想转成文字的需求时,比如一段音频的课程,或者是一段会议的录音,可以采取非常原始的方法,就是一边听,一边打字,实现「同声转写」(雾),也可以借助AI的力量,调用百度语音识别的接口,通过代码将音频转换成文字,高效便捷。

二、技术方案简介:

目前百度语音识别可以选择的接口有:短语音识别,实时语音识别,音频文件转写。这里简单对三种接口进行分析:

短语音识别:要求音频文件小于60秒,有长度限制;

实时语音识别:要求持续传音频数据帧,识别多长的音频,就需要花多长的时间,而且有一小时的音频时长限制;

音频文件转写:要求音频文件上传到公网,而且识别是异步的任务,耗时不一定;

为了识别长音频文件,并且只花较短的时间,可以将音频文件拆分成小于60秒的一个一个的音频文件,然后循环请求短语音识别接口,如果对速度有更高的要求,可以并发请求接口,进一步缩短整体的耗时。

三、具体的实现步骤

话不多说,直接上代码:

# coding=utf-8

import requests
import sys
import base64
from pydub import AudioSegment
from pydub.utils import make_chunks


# 获取access token
def fetch_token(ak, sk):
    __token_url = 'http://aip.baidubce.com/oauth/2.0/token'
    params = {
        'grant_type': 'client_credentials',
        'client_id': ak,
        'client_secret': sk
    }
    result = requests.post(__token_url, data=params)
    if result.status_code == 200:
        return result.json()['access_token']
    else:
        print("get access_token failed:", result.json())


# 读取音频文件
def get_file_content(file_path):
    with open(file_path, 'rb') as fp:
        return fp.read()

# 使用pydub库拆分音频文件,size=秒*1000
def split_audio(audio_file, size=59000):
    audios = []
    audio_name = audio_file[:-4]
    audio_format = audio_file[-3:]
    print(audio_name, audio_format)
    audio = AudioSegment.from_file(audio_file, audio_format)
    chunks = make_chunks(audio, size)
    print(chunks)
    i = 0
    for chunk in chunks:
        chunk_name = '{}-{}.{}'.format(audio_name, i, 'wav')
        chunk = chunk.set_frame_rate(16000).set_channels(1)
        chunk.export(chunk_name, format='wav', )
        i += 1
        audios.append(chunk_name)
    return audios


# 调用短语音识别接口,可将识别结果追加只text_file文件中
def asr(access_token, audio_file, text_file=None):
    __asr_url = 'http://vop.baidu.com/server_api'
    speech = get_file_content(audio_file)
    data = {}
    data['speech'] = base64.b64encode(speech).decode()
    data['len'] = len(speech)
    data['channel'] = 1
    data['format'] = audio_file[-3:]
    data['rate'] = 16000
    data['cuid'] = 'baidu'
    data['token'] = access_token
    result = requests.post(__asr_url, json=data)
    if result.status_code == 200:
        text = ''.join(result.json()['result'])
    else:
        print("asr failed:", result.json())
    if text_file and os.path.isfile(text_file):
        with open(text_file, 'a') as f:
            f.write(text)
            f.write('\n')
    else:
        return text

if __name__ == '__main__':
    ak = 'EicDkBVuZAEhK4xxxxxxx'
    sk = '3tv17TseMPov7pvXHmWfxxxxxxxx'
    token = fetch_token(ak, sk)
    print(token)
    audio_file = '../data/audio.m4a'
    audios = split_audio(audio_file)
    for audio in audios:
        asr(token, audio, 'text.txt')

四、实现的效果:

原音频文件,和拆分后的单个文件,以及结果文件截图:

识别结果截图:

五、总结:

IDE使用的pycharm,使用了ffmpeg做为底层工具进行音频文件转码切分,使用requests库发起post请求去获取access token,请求短语音识别的api接口,使用pydub库对音频文件进行切分和转码。

整体的流程就是:

  1. 注册百度智能云的账号
  2. 完成个人实名认证
  3. 领取语音识别-短语音识别-中文普通话接口免费额度
  4. 安装ffmpeg
  5. pycharm安装requests和pydub库
  6. 参考文档进行编码

时间仓促,代码没有仔细打磨,多线程请求接口功能没有实现,仅供大家参考~

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共2条回复 最后由mcphws0035回复于2023-02
#21mcphws0035回复于2023-02

视频转音频AudioFileClip 转的wav文件

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#20梦回清元回复于2023-01

大佬,为啥我的识别效果很差,就没有对上的。我是用的【朱广权的新闻视频】,视频转音频AudioFileClip 转的wav文件,然后调用了【短语音识别】,是我提供的wav文件有问题吗

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