* 👋 Hello! This is an ml5.js example made and shared with ❤️.

 * Learn more about the ml5.js project: https://ml5js.org/

 * ml5.js license and Code of Conduct: https://github.com/ml5js/ml5-next-gen/blob/main/LICENSE.md

 *

 * This example demonstrates Sound classification using Google's Teachable Machine and p5.js

 * Create your own custom model with Google's Teachable Machine! https://teachablemachine.withgoogle.com/

 */

​

// Initialize a sound classifier method with SpeechCommands18w model. A callback needs to be passed.

let classifier;

​

// Variable for holding the results of the classification

let predictedSound = "";

​

// Link to custom Teachable Machine model

const modelJson = "https://teachablemachine.withgoogle.com/models/n702_a7ev/";

​

​

let x = 40,

  y = 40;

let n = 3;

let n2 = 3;

let n3 = 3;

let numSentences1 = 2;

let numSentences2 = 3;

let numSentences3 = 3;

let displayText = [""];

​

let markov;

let markov2;

let markov3;

let source1;

let source2;

let source3;

​

let moon;

let bakunawa;

let miniMoon;

​

let words = [

  "Love",

  "Pain",

  "Power",

  "Heaven",

  "Earth",

  "Creatures",

  "Instincts",

  "Soul",

  "Voice",

];

​

​

let play = true;

let counter = 0;

let keywordDetected = false;

​

function preload() {

  // Load Teachable Machine model

  classifier = ml5.soundClassifier(modelJson);

  moon = loadImage("moon.png");

  miniMoon = loadImage("miniMoon.png");

  bakunawa = loadImage("bakunawa.png");

​

  source1 = loadStrings("source1.txt");

  source2 = loadStrings("source2.txt");

  source3 = loadStrings("source3.txt");

}

​

function setup() {

  createCanvas(500, 500);

  // textAlign(CENTER, CENTER);

  // textSize(32);

​

  // Classify the sound from microphone in real time

  classifier.classifyStart(gotResult);

​

  // create markov models

  markov = RiTa.markov(n);

  markov2 = RiTa.markov(n2);

  markov3 = RiTa.markov(n3);

​

  // load text into the models

  markov.addText(source1.join(" "));

  markov2.addText(source2.join(" "));

  markov3.addText(source3.join(" "));

}

​

function draw() {

  background(0);

  textFont('Courier New');

  if (!keywordDetected) { // if keyword not detected

    showIntroScreen(); // show intro

  } else {

    generateMessageFromKeywords(); // show message

  }

}

​

function showIntroScreen() {

    fill(255);

    textSize(16);

    textAlign(CENTER);

    text('Offer a prayer for the collective using one of these words:',40 , 50, 400);

    textSize(30);

    textFont("Bungee Hairline")

    text('Love, Pain, Power', width / 2, 180); 

  text('Heaven, Earth, Creatures', width / 2, 240); 

    text('Instincts, Soul, Voice', width / 2, 300); 

}

​

function generateMessageFromKeywords() {

   if (predictedSound == "Moon") {

    background(231, 176, 255);

    displayText = markov3.generate(numSentences3);

    image(moon, 0, 0, 500, 500);

    text(displayText.join(" "), x, y, width / 2 - 210, y, 420, 440);

  } else if (predictedSound == "miniMoon") {

    background(255, 242, 143);

    displayText = markov2.generate(numSentences2);

    image(miniMoon, 0, 0, 500, 500);

    text(displayText.join(" "), x, y, width / 2 - 210, y, 420, 440);

  } else if (predictedSound == "Bakunawa") {

    background(255, 242, 143);

    displayText = markov.generate(numSentences1);

    image(bakunawa, 0, 0, 500, 500);

    text(displayText.join(" "), x, y, width / 2 - 210, y, 420, 440);

  }

    counter = counter + 1;

    if (counter > 600) {

      play = false;

      keywordDetected = false;

      counter = 0;

    }

}

​

function gotResult(error, results) {

  if (error) {

    console.error(error);

    return;

  }

​

  // Print the whole structure of the results to inspect it

  console.log("Results Array:", results);

  console.log("Results Structure:", JSON.stringify(results, null, 2));

​

  // Check if the array contains valid objects and inspect each object

  if (results && Array.isArray(results) && results.length > 0) {

    results.forEach((result, index) => {

      console.log(`Result ${index}:`, result); // Log the object itself to see its structure

    });

  }

​

  // Now, process the results

  if (results && results[0] && results[0].label) {

    predictedSound = results[0].label;

    let confidence = results[0].confidence;

​

    console.log(`Predicted Sound: ${predictedSound}, Confidence: ${confidence}`);

​

    // Trigger message if confidence is high enough

    if (confidence > 0.75 && (predictedSound === "Moon" || predictedSound === "miniMoon" || predictedSound === "Bakunawa")) {

      keywordDetected = true;

      console.log("Keyword detected with sufficient confidence, triggering message...");

    } else {

      console.log("No keyword detected or confidence too low.");

    }

  } else {

    console.log("No valid prediction found in results.");

  }

}

​

// // A function to run when we get any errors and the results

// function gotResult(error, results) {

//   if (error) {

//     console.log(error);

//     return;

//   }

//   predictedSound = results[0].label;

//   // The results are in an array ordered by confidence.

//  if (predictedSound === "Moon" || predictedSound === "miniMoon" || predictedSound === "Bakunawa") {

//     keywordDetected = true; //trigger message

//   }

// }

​