使用百度ai接口加图灵机器人完成简单web版语音对话

app文件

from flask import Flask, request, render_template, jsonify, send_file
from uuid import uuid4
import os
import asr_test

app = Flask(__name__)
app.debug = True


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


@app.route('/uploader', methods=['POST'])
def uploader():
    file = request.files.get('reco')
    file_name = os.path.join('audio', f'{uuid4()}.wav')
    file.save(file_name)
    ret_filename = asr_test.my_ai(file_name)
    print(ret_filename)
    return jsonify({'filename': ret_filename})


@app.route('/get_audio/<filename>')
def get_audio(filename):
    file = os.path.join('audio', filename)
    return send_file(file)


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

调用百度语音识别与语音合成接口，把传来的语言识别成文字，并调用下面的相似度接口，返回回答的文字，然后利用语音合成返回回答

from aip import AipSpeech
import os
from my_npl import get_score
from uuid import uuid4

""" 你的 APPID AK SK """
APP_ID = '******'
API_KEY = '******'
SECRET_KEY = '******'

client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)


# 读取文件
def get_file_content(filePath):
    any2pcm_str = f"ffmpeg -y  -i {filePath} -acodec pcm_s16le -f s16le -ac 1 -ar 16000 {filePath}.pcm"
    os.system(any2pcm_str)
    with open(f"{filePath}.pcm", 'rb') as fp:
        return fp.read()


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

    print(res.get('result'))
    print(res)
    question = res.get('result')[0]
    req = get_score(question)

    req = client.synthesis(req, 'zh', 1, {
        'vol': 5,
        'pit': 5,
        'spd': 4,
        "per": 4
    })

    # 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(req, dict):
        ret_filename = f'{uuid4()}.mp3'
        new_filename = os.path.join("audio", ret_filename)
        with open(new_filename, 'wb') as f:
            f.write(req)
        return ret_filename

调用百度ai自然语言中的短文本相似度接口，使相似的问题得到相同的答案

from aip import AipNlp
from mytuling import to_tuling

""" 你的 APPID AK SK """
APP_ID = '***'
API_KEY = '***'
SECRET_KEY = '***'

client = AipNlp(APP_ID, API_KEY, SECRET_KEY)


def get_score(Q):
    if client.simnet(Q, '你叫什么名字').get('score') > 0.7:
        return '我是大名鼎鼎的小王吧'
    elif client.simnet(Q, '你今年几岁呀').get('score') > 0.7:
        return '我今年已经1112岁啦'
    else:
        return to_tuling(Q)

调用图灵接口完成未设定问答的

import requests

tuling_url = 'http://openapi.tuling123.com/openapi/api/v2'

data = {"reqType": 0,
        "perception": {
            "inputText": {
                "text": ""
            }
        }
    ,
        "userInfo": {
            "apiKey": "***",
            "userId": "***"
        }
        }


def to_tuling(Q):
    data["perception"]["inputText"]['text'] = Q
    a = requests.post(url=tuling_url, json=data)
    res = a.json()
    print(res)
    return res.get("results")[0].get("values").get("text")

简单前端页面

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Title</title>
</head>
<body>
<audio src="" autoplay controls id="player"></audio>
<p>
    <button onclick="start_reco()">开始录音</button>
</p>
<p>
    <button onclick="stop_reco()">停止录音</button>
</p>

</body>
<script src="/static/Recorder.js"></script>
<script src="/static/jQuery3.1.1.js"></script>
<script type="text/javascript">
    var serv = "http://127.0.0.1:5000";
    var audio_serv = serv + "/get_audio/";
    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() {
        reco.stop();
        get_audio();
        reco.clear();
    }

    function get_audio() {
        reco.exportWAV(function (wav_file) {
            // wav_file 音频文件 Blob("wav","context")
            console.log(wav_file);
            var formdata = new FormData();
            formdata.append("reco", wav_file);
            $.ajax({
                    url: serv + "/uploader",
                    type: 'post',
                    processData: false,
                    contentType: false,
                    data: formdata,
                    dataType: 'json',
                    success: function (data) {
                        document.getElementById("player").src = audio_serv + data.filename;
                    }
                }
            );
        })
    }
</script>
</html>

前端页面