人工智障

1.百度的语音合成

具体配置参考 http://ai.baidu.com/docs#/TTS-Online-Python-SDK/top

from aip import AipSpeech

""" 你的 APPID AK SK """
APP_ID = '15421010'
API_KEY = 'YSKSaidmdyWkfhnhWezCeTqi'
SECRET_KEY = 'EXfzsG9tr6fI6U4KPz28XQmXa8MIBKMz'

client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)

result = client.synthesis('来到这个世界，天使都会犯错', 'zh', 1, {
    'vol': 5,
})

# 识别正确返回语音二进制 错误则返回dict 参照下面错误码
if not isinstance(result, dict):
    with open('audio.mp3', 'wb') as f:
        f.write(result)

2.百度的语音识别

具体配置参考 http://ai.baidu.com/docs#/ASR-Online-Python-SDK/top

import os
from aip import AipSpeech

""" 你的 APPID AK SK """
APP_ID = '15421010'
API_KEY = 'YSKSaidmdyWkfhnhWezCeTqi'
SECRET_KEY = 'EXfzsG9tr6fI6U4KPz28XQmXa8MIBKMz'

client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)

# 读取文件
def get_file_content(filePath):
    os.system(f"ffmpeg -y  -i {filePath} -acodec pcm_s16le -f s16le -ac 1 -ar 16000 {filePath.split('.')[0]}.pcm") #执行的是一个对文件格式的转换，需要下载一个ffmgep
    with open(f"{filePath.split('.')[0]}.pcm", 'rb') as fp:
        return fp.read()

# 识别本地文件
res = client.asr(get_file_content('jrshdls.m4a'), 'pcm', 16000, {
    'dev_pid': 1536,
})

print(res)

3.两个结合

import os
import time
from aip import AipSpeech

""" 你的 APPID AK SK """
APP_ID = '15421010'
API_KEY = 'YSKSaidmdyWkfhnhWezCeTqi'
SECRET_KEY = 'EXfzsG9tr6fI6U4KPz28XQmXa8MIBKMz'

client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)


# 读取文件
def get_file_content(filePath):
    os.system(f"ffmpeg -y  -i {filePath} -acodec pcm_s16le -f s16le -ac 1 -ar 16000 {filePath.split('.')[0]}.pcm")
    with open(f"{filePath.split('.')[0]}.pcm", 'rb') as fp:
        return fp.read()


def audio2text(filepath):
    # 识别本地文件
    res = client.asr(get_file_content(filepath), 'pcm', 16000, {
        'dev_pid': 1536,
    })
    print(res.get("result")[0])
    return res.get("result")[0]


def text2audio(text):
    filename = f"{time.time()}.mp3"
    result = client.synthesis(text, 'zh', 1, {
        'vol': 5,
    })
    # 识别正确返回语音二进制 错误则返回dict 参照下面错误码
    if not isinstance(result, dict):
        with open(filename, 'wb') as f:
            f.write(result)
    return filename


text = audio2text("jrshdls.m4a")
filename = text2audio(text)

os.system(filename)

4.图灵机器人的简单使用

具体参考 https://www.kancloud.cn/turing/www-tuling123-com/718227

import requests


args = {
    "reqType":0,
    "perception": {
        "inputText": {
            "text": "附近的酒店"
        }
    },
    "userInfo": {
        "apiKey": "08a682c47e334a11bd99cbf093930b63",
        "userId": "1"
    }
}

url = "http://openapi.tuling123.com/openapi/api/v2"

res = requests.post(url, json=args)

print(res.json())

5.人工智障的简单应用

import os
import time
from aip import AipSpeech, AipNlp #提供自认语言处理

""" 你的 APPID AK SK """
APP_ID = '15421010'
API_KEY = 'YSKSaidmdyWkfhnhWezCeTqi'
SECRET_KEY = 'EXfzsG9tr6fI6U4KPz28XQmXa8MIBKMz'

client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)
nlp = AipNlp(APP_ID, API_KEY, SECRET_KEY) #自认语言处理


# 读取文件
def get_file_content(filePath):
    os.system(f"ffmpeg -y  -i {filePath} -acodec pcm_s16le -f s16le -ac 1 -ar 16000 {filePath.split('.')[0]}.pcm")
    with open(f"{filePath.split('.')[0]}.pcm", 'rb') as fp:
        return fp.read()


def audio2text(filepath):
    # 识别本地文件
    res = client.asr(get_file_content(filepath), 'pcm', 16000, {
        'dev_pid': 1536,
    })
    print(res.get("result")[0])
    return res.get("result")[0]


def text2audio(text):
    filename = f"{time.time()}.mp3"
    result = client.synthesis(text, 'zh', 1, {
        'vol': 5,
    })
    # 识别正确返回语音二进制 错误则返回dict 参照下面错误码
    if not isinstance(result, dict):
        with open(filename, 'wb') as f:
            f.write(result)
    return filename

# print(nlp.simnet("你叫什么名字", "你的名字是什么"))

text = audio2text("jrshdls.m4a")
if nlp.simnet("时间的多少", text).get("score") >= 0.68: #这个方法会匹配两个字符串的相似度
    text = "我的名字是小明"
else:
    text = "我不知道你在说什么"
filename = text2audio(text)

os.system(filename)

 6.如何在浏览器中实现图灵机器人的对话

baidu_ai.py

import os
import time
from aip import AipSpeech, AipNlp

""" 你的 APPID AK SK """
APP_ID = '15421010'
API_KEY = 'YSKSaidmdyWkfhnhWezCeTqi'
SECRET_KEY = 'EXfzsG9tr6fI6U4KPz28XQmXa8MIBKMz'

client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)
nlp = AipNlp(APP_ID, API_KEY, SECRET_KEY)


# 读取文件
def get_file_content(filePath):
    os.system(f"ffmpeg -y  -i {filePath} -acodec pcm_s16le -f s16le -ac 1 -ar 16000 {filePath.split('.')[0]}.pcm")
    with open(f"{filePath.split('.')[0]}.pcm", 'rb') as fp:
        return fp.read()


def audio2text(filepath):
    # 识别本地文件
    res = client.asr(get_file_content(filepath), 'pcm', 16000, {
        'dev_pid': 1536,
    })
    print(res.get("result")[0])
    return res.get("result")[0]


def text2audio(text):
    filename = f"{time.time()}.mp3"
    result = client.synthesis(text, 'zh', 1, {
        'vol': 5,
    })
    # 识别正确返回语音二进制 错误则返回dict 参照下面错误码
    if not isinstance(result, dict):
        with open(filename, 'wb') as f:
            f.write(result)
    return filename


def to_tuling(text):
    import requests

    args = {
        "reqType": 0,
        "perception": {
            "inputText": {
                "text": text
            }
        },
        "userInfo": {
            "apiKey": "08a682c47e334a11bd99cbf093930b63",
            "userId": "1"
        }
    }

    url = "http://openapi.tuling123.com/openapi/api/v2"
    res = requests.post(url, json=args)
    text = res.json().get("results")[0].get("values").get("text")
    return text

app.py

from flask import Flask, request, render_template, jsonify, send_file
import baidu_ai
from uuid import uuid4

app = Flask(__name__)


@app.route("/")
def index():
    return render_template("index.html")


@app.route("/ai", methods=["POST"])
def ai():
    # 1.保存录音文件
    audio = request.files.get("record")
    filename = f"{uuid4()}.wav"
    audio.save(filename)
    # 2.将录音文件转换为PCM发送给百度进行语音识别
    q_text = baidu_ai.audio2text(filename)

    # 3.将识别的问题交给图灵或自主处理获取答案
    a_text = baidu_ai.to_tuling(q_text)

    # 4.将答案发送给百度语音合成，合成音频文件
    a_file = baidu_ai.text2audio(a_text)

    # 5.将音频文件发送给前端播放

    return jsonify({"filename": a_file})


@app.route("/get_audio/<filename>")
def get_audio(filename):
    return send_file(filename)


if __name__ == '__main__':
    app.run("0.0.0.0", 5000, debug=True)

index.html

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Title</title>
</head>
<body>
<audio controls autoplay id="player"></audio>
<p>
    <button onclick="start_reco()" style="background-color: yellow">录制语音指令</button>
</p>
<p>
    <button onclick="stop_reco_audio()" style="background-color: blue">发送语音指令</button>
</p>
</body>
<!--<script type="application/javascript" src="/static/Recorder.js"></script>-->
<script type="application/javascript" src="https://cdn.bootcss.com/recorderjs/0.1.0/recorder.js"></script>
<script type="text/javascript" src="/static/jQuery3.1.1.js"></script>

<script type="text/javascript">
    var reco = null;
    var audio_context = new AudioContext();
    navigator.getUserMedia = (navigator.getUserMedia ||
        navigator.webkitGetUserMedia ||
        navigator.mozGetUserMedia ||
        navigator.msGetUserMedia);

    navigator.getUserMedia({audio: true}, create_stream, function (err) {
        console.log(err)
    });

    function create_stream(user_media) {
        var stream_input = audio_context.createMediaStreamSource(user_media);
        reco = new Recorder(stream_input);
    }

    function start_reco() {
        reco.record();
    }


    function stop_reco_audio() {
        reco.stop();
        send_audio();
        reco.clear();
    }


    function send_audio() {
        reco.exportWAV(function (wav_file) {
            var formdata = new FormData();
            formdata.append("record", wav_file);
            console.log(formdata);
            $.ajax({
                url: "http://192.168.13.177:5000/ai",
                type: 'post',
                processData: false,
                contentType: false,
                data: formdata,
                dataType: 'json',
                success: function (data) {
                    console.log(data);
                    document.getElementById("player").src ="http://192.168.13.177:5000/get_audio/" + data.filename
                }
            });

        })
    }



</script>
</html>