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viseme3d_backend
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// azure-cognitiveservices-speech.js
require('dotenv').config()
const sdk = require('microsoft-cognitiveservices-speech-sdk');
const blendShapeNames = require('./blendshapeNames');
const _ = require('lodash');

let SSML = `<speak version="1.0" xmlns="http://www.w3.org/2001/10/synthesis" xmlns:mstts="http://www.w3.org/2001/mstts" xml:lang="en-US">
<voice name="en-US-JennyNeural">
  <mstts:viseme type="FacialExpression"/>
  __TEXT__
</voice>
</speak>`;

const key = process.env.AZURE_KEY;
const region = process.env.AZURE_REGION;
        
/**
 * Node.js server code to convert text to speech
 * @returns stream
 * @param {*} key your resource key
 * @param {*} region your resource region
 * @param {*} text text to convert to audio/speech
 * @param {*} filename optional - best for long text - temp file for converted speech/audio
 */
const textToSpeech = async (text, voice)=> {
    
    // convert callback function to promise
    return new Promise((resolve, reject) => {
        

        let ssml = SSML.replace("__TEXT__", text);

        
        const speechConfig = sdk.SpeechConfig.fromSubscription(key, region);
        speechConfig.speechSynthesisOutputFormat = 5; // mp3
        
        let audioConfig = null;
        
        // if (filename) {
        let randomString = Math.random().toString(36).slice(2, 7);
        let filename = `./public/speech-${randomString}.mp3`;
        audioConfig = sdk.AudioConfig.fromAudioFileOutput(filename);
        // }

        let blendData = [];
        let timeStep = 1/60;
        let timeStamp = 0;

        const synthesizer = new sdk.SpeechSynthesizer(speechConfig, audioConfig);

        // Subscribes to viseme received event
        synthesizer.visemeReceived = function (s, e) {

            // `Animation` is an xml string for SVG or a json string for blend shapes
            var animation = JSON.parse(e.animation);

            _.each(animation.BlendShapes, blendArray => {

                let blend = {};
                _.each(blendShapeNames, (shapeName, i) => {
                    blend[shapeName] = blendArray[i];
                });
        
                blendData.push({
                    time: timeStamp,
                    blendshapes: blend
                });
                timeStamp += timeStep;
            });

        }


        synthesizer.speakSsmlAsync(
            ssml,
            result => {
                
                synthesizer.close();
                resolve({blendData, filename: `/speech-${randomString}.mp3`});

            },
            error => {
                synthesizer.close();
                reject(error);
            }); 
    });
};

module.exports = textToSpeech;