dyte-proctoring/
├── frontend
│ ├── README.md
│ ├── package.json
│ ├── public
│ ├── src
│ │ ├── App.css
│ │ ├── App.jsx
│ │ ├── Heading.jsx
│ │ ├── ImageInput.jsx
│ │ ├── Meet.jsx
│ │ ├── Proctor.jsx
│ │ ├── index.css
│ │ ├── index.jsx
│ │ ├── logo.svg
│ │ ├── react-app-env.d.ts
│ │ ├── reportWebVitals.ts
│ │ ├── setupTests.ts
│ │ ├── stage.jsx
│ │ └── utils.js
│ ├── tsconfig.json
├── venv
├── app.py
├── audio_diarization.py
└── requirements.txt
By the end of this tutorial, we would have built a “Live Proctoring System” using Dyte APIs that allows the admin to monitor whether multiple speakers can be heard from a candidate’s microphone. 👀🧑💻
Introduction
In the early days of online education, as the need arose to maintain the integrity of exams, proctoring emerged as a trusted monitoring method to prevent students from engaging in dishonest behavior. As the digital landscape expanded and online courses became more prevalent, the traditional ways of proctoring started to show their limitations.
Consider online exams, where having a physical proctor for every student becomes impractical. This gave rise to the adoption of live automatic proctoring.
This modern approach harnesses the power of a student’s webcam and microphone to oversee the exam process. By incorporating computer vision and machine learning, it efficiently detects cheating attempts.
In this tutorial, we’ll create a live proctoring system using Dyte APIs, enabling an admin to detect the presence of multiple speakers in a candidate’s background throughout the exam in real-time. ✨
High-Level Design of the application
Our aim is to notify the proctor if we hear multiple voices from the candidate’s background.
The proctor would get the candidate's details right in his meeting sidebar. 🔊✨
- In this project, we will use React with Dyte UI kit and Dyte React Web Core packages for the frontend.
- For the backend, we will use FastApi (Python 3).
- We will also use database as a service by ElephantSQL (PostgreSQL).
- Lastly, we will be using Deepgram Audio Diarization APIs to get speaker details from a sample audio clip.
Folder Structure
After completing the tutorial, the folder structure will look like this. 👇
Step 0: Configurations and Setup
🧑💻 Before building our live proctoring system, we must set up a Dyte account.
We can create a free account by clicking the "Start Building" button on Dyte.io and signing up using Google or GitHub. 🎉
Once signed up, we can access our Dyte API keys from the "API Keys" tab in the left sidebar. We will keep these keys secure as we will use them later. 🔑🤫
For our live proctoring system, we will use React for the frontend and FastAPI for building the Backend and APIs.
We will begin by creating a new directory for our project, called dyte-proctoring, and navigating into it using the following commands:
mkdir dyte-proctoring
cd dyte-proctoring
NOTE
We will require to create accounts on the following platforms:
- ElephantSQL: Here is a step-by-step guide to create a db on ElephantSQL.
- Deepgram: Here is a step-by-step guide to start using Deepgram.
Now back to the tutorial.
Step 1: Setting up the Frontend
Let's start setting up our frontend project using React and Dyte! ✨
We will create a boilerplate React app using create-react-app. We can do this with the following command:
yarn create react-app frontend
This will initialize a new React app in the frontend directory. 📁
Then, we will go ahead and install the dyte react-web-core, dyte react-ui-kit and react-router packages in this project using the following command 👇
yarn add @dytesdk/react-web-core @dytesdk/react-ui-kit react-router react-router-dom
Step 2: Setting up the backend
Let's get started with setting up our FastAPI backend now. 🙌
We will go back to the root directory of our project and initiate our project here itself for the ease of hosting:
cd ..
First of all, we will go ahead and create our requirements.txt file in the root directory itself with the following content 👇
requirements.txt
cmake
fastapi
uvicorn
face_recognition
numpy
python-multipart
psycopg2-binary
httpx
python-dotenv
pydantic
requests
After this, we will go ahead and create our virtual environment with venv and install the dependencies.
python -m venv venv
source venv/bin/activate # for linux/mac
venv\Scripts\activate.bat # for windows
pip install -r requirements.txt
We will also create an environment variable file .env, for storing our credentials.
.env
DYTE_ORG_ID=<ID>
DYTE_API_KEY=<KEY>
IMGUR_CLIENT_ID=<ID>
DB_USER=<ID>
DB_PASSWORD=<PASSWORD>
DB_HOST=<HOST>
DEEPGRAM_API_KEY=<API_KEY>
Step 3: Setting up our backend application
Now, we will create a new file named app.py and add our 🐘 ElephantSQL PostgreSQL database connection and code for our APIs, including face detection logic.
In this file, we would need to create the following routes:
GET / - Root route
POST /is_admin/ - Check if the user is an admin
POST /multiple_voices_list/ - This route retrieves a list of participants who are detected as suspicious
POST /multiple_voices/ - Detect if there are multiple voices in the audio stream
POST /meetings - Create a new meeting
POST /meetings/{meetingId}/participants - This route is responsible for adding a participant to a specific meeting identified by meetingId
So let’s get started 👇
app.py
import base64
import io
import logging
import random
import requests
import uvicorn
from fastapi import FastAPI, Form, UploadFile, File
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
import psycopg2
from utils import upload_audio
import os
import base64
from fastapi import FastAPI, HTTPException
from dotenv import load_dotenv
from httpx import AsyncClient
import httpx
import uuid
from audio_diarization import speakers_count
load_dotenv()
DYTE_API_KEY = os.getenv("DYTE_API_KEY")
DYTE_ORG_ID = os.getenv("DYTE_ORG_ID")
API_HASH = base64.b64encode(f"{DYTE_ORG_ID}:{DYTE_API_KEY}".encode('utf-8')).decode('utf-8')
timeout = httpx.Timeout(10.0, read=None)
DYTE_API = AsyncClient(base_url='https://api.cluster.dyte.in/v2', headers={'Authorization': f"Basic {API_HASH}"}, timeout=timeout)
logger = logging.getLogger(name)
logging.basicConfig(level=logging.INFO)
fh = logging.FileHandler("app.log")
fh.setLevel(logging.DEBUG)
formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
fh.setFormatter(formatter)
logger.addHandler(fh)
class ProctorPayload(BaseModel):
meeting_id: str
admin_id: str
class AdminProp(BaseModel):
meeting_id: str
admin_id: str
class Meeting(BaseModel):
title: str
class Participant(BaseModel):
name: str
preset_name: str
meeting_id: str
origins = [
# allow all
"*",
]
app = FastAPI()
enable cors
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=[""], # allow all
allow_headers=[""], # allow all
)
def connect_to_db():
conn = psycopg2.connect(
dbname=os.getenv('DB_USER'),
user=os.getenv('DB_USER'),
password=os.getenv('DB_PASSWORD'),
host=os.getenv('DB_HOST'),
port=5432
)
return conn
@app.get("/")
async def root():
return {"message": "Hello World"}
@app.post("/is_admin/")
async def multiple_faces_list(admin: AdminProp):
conn = connect_to_db()
cur = conn.cursor()
cur.execute("SELECT count(1) FROM meeting_host_info WHERE meeting_id = %s AND admin_id = %s", (admin.meeting_id, admin.admin_id,))
count = cur.fetchone()[0]
if(count > 0):
return { "admin": True }
else:
return { "admin": False }
@app.post("/multiple_voices_list/")
async def multiple_faces_list(meeting: ProctorPayload):
conn = connect_to_db()
cur = conn.cursor()
cur.execute("SELECT count(1) FROM meeting_host_info WHERE meeting_id = %s AND admin_id = %s", (meeting.meeting_id, meeting.admin_id,))
count = cur.fetchone()[0]
if(count > 0):
cur.execute("CREATE TABLE IF NOT EXISTS meeting_audio_proc_details (ts TIMESTAMP, meeting_id VARCHAR(255), participant_id VARCHAR(255), audio_url VARCHAR(255), verdict VARCHAR(255))")
cur.execute("SELECT * FROM meeting_audio_proc_details WHERE meeting_id = %s ORDER BY ts DESC", (meeting.meeting_id,))
rows = cur.fetchall()
conn.commit()
cur.close()
conn.close()
return rows
else:
conn.commit()
cur.close()
conn.close()
raise HTTPException(status_code=401, detail="Participant dose not has admin role")
@app.post("/multiple_voices/")
async def multiple_voices(file: UploadFile = File(...), meeting_id: str = Form(...), participant_id: str = Form(...), participant_name: str = Form(...)):
contents = file.file.read()
filename = file.filename.split('.')[0] + str(random.randint(1, 100)) + '.mp3'
with open(filename, 'wb') as f:
f.write(contents)
file.file.close()
conn = connect_to_db()
cur = conn.cursor()
cur.execute("CREATE TABLE IF NOT EXISTS meeting_audio_proc_details (ts TIMESTAMP, meeting_id VARCHAR(255), participant_id VARCHAR(255), audio_url VARCHAR(255), verdict VARCHAR(255))")
try:
count = speakers_count(filename)
except Exception as e:
logger.error(e)
if count > 1:
logger.info(
f"Detected different voices for participant {participant_id}"
)
verdict = f"Participant Name: {participant_name} <> Anomaly: Different Voices Detected <> Participant ID: {participant_id}"
cur.execute("SELECT count(1) FROM meeting_audio_proc_details WHERE meeting_id=%s AND participant_id=%s AND ts >= (current_timestamp - INTERVAL '10 minutes')", (meeting_id, participant_id))
count = cur.fetchone()[0]
if count == 0:
# if there is a requirement of storing audio files
upload_resp = await upload_audio(img_data)
cur.execute("INSERT INTO meeting_audio_proc_details (ts, meeting_id, participant_id, audio_url, verdict) VALUES (current_timestamp, %s, %s, %s, %s)",
(meeting_id, participant_id, upload_resp, verdict)
)
conn.commit()
cur.close()
conn.close()
if count == 0:
return { "id": participant_id, "different_voices_detected": True, "url": upload_resp }
return { "id": participant_id, "different_voices_detected": True, "url": "not uploaded" }
return {"id": participant_id, "different_voices_detected": False}
@app.post("/meetings")
async def create_meeting(meeting: Meeting):
response = await DYTE_API.post('/meetings', json=meeting.dict())
if response.status_code >= 300:
raise HTTPException(status_code=response.status_code, detail=response.text)
admin_id = ''.join(random.choices('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789', k=32))
resp_json = response.json()
resp_json['admin_id'] = admin_id
meeting_id = resp_json['data']['id']
conn = connect_to_db()
cur = conn.cursor()
cur.execute("INSERT INTO meeting_host_info (ts, meeting_id, admin_id) VALUES (CURRENT_TIMESTAMP, %s, %s)", (meeting_id, admin_id))
conn.commit()
cur.close()
conn.close()
return resp_json
@app.post("/meetings/{meetingId}/participants")
async def add_participant(meetingId: str, participant: Participant):
client_specific_id = f"react-samples::{participant.name.replace(' ', '-')}-{str(uuid.uuid4())[0:7]}"
payload = participant.dict()
payload.update({"client_specific_id": client_specific_id})
del payload['meeting_id']
resp = await DYTE_API.post(f'/meetings/{meetingId}/participants', json=payload)
if resp.status_code > 200:
raise HTTPException(status_code=resp.status_code, detail=resp.text)
return resp.text
if name == "main":
uvicorn.run("app:app", host="localhost", port=8000, log_level="debug", reload=True)
This code defines a ⚡️ FastAPI application with an endpoint /multiple_voices, which takes in an audio file in binary format and returns a boolean value indicating if there are multiple voices in the audio submitted.
It uses the audio_diarization api by Deepgram API service to detect multiple voices in the audio received.
audio_diarization.py
import os
from httpx import AsyncClient
import requests
from dotenv import load_dotenv
load_dotenv()
DEEPGRAM_API_KEY = os.getenv("DEEPGRAM_API_KEY")
DEEPGRAM_API = AsyncClient(base_url='https://api.deepgram.com/v1', headers={'Authorization': f"Token {DEEPGRAM_API_KEY}", 'Content-Type': "audio/mp3"})
def speakers_count(audio_file_path):
speaker_set = set()
audio = open(audio_file_path, 'rb')
response = requests.post('https://api.deepgram.com/v1/listen?diarize=true', data=audio, headers={'Authorization': f"Token {DEEPGRAM_API_KEY}", 'Content-Type': "audio/mp3"})
resp_json = response.json()
statements = resp_json['results']['channels'][0]['alternatives']
for statement in statements:
words = statement['words']
for word in words:
speaker_set.add(word['speaker'])
return len(speaker_set)
The code also makes use of the Dyte API for meeting-related operations. 📹
We can start the backend server simply by using the following command:
python app.py
This Python server helps us create and join meetings, detect different faces, and get the list of suspicious candidates. 🕵️
Here, when we hit the /multiple_voices endpoint with an audio file, the multiple_voices_detected key of the response would be set to True if there are multiple voices in the audio file received, else it will be set to False.
We can call this from our frontend with the participant’s mic.
With this sorted, let's return to our React application and create our UI. ✨
Step 4: Setting up the Meeting UI
First, let us add our CSS file, create a new file frontend/src/App.css and paste the following code.
.App {
text-align: center;
}
.App-logo {
height: 40vmin;
pointer-events: none;
}
@media (prefers-reduced-motion: no-preference) {
.App-logo {
animation: App-logo-spin infinite 20s linear;
}
}
.App-header {
background-color: #282c34;
min-height: 100vh;
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
font-size: calc(10px + 2vmin);
color: white;
}
.App-link {
color: #61dafb;
}
.heading-proctor {
font-size: x-large;
font-weight: bolder;
color: #fff;
}
@keyframes App-logo-spin {
from {
transform: rotate(0deg);
}
to {
transform: rotate(360deg);
}
}
.file-input label {
margin-top: 20px;
display: block;
position: relative;
width: 200px;
height: 50px;
border-radius: 10px;
background-color: #2160fd;
display: flex;
align-items: center;
justify-content: center;
flex-direction: row;
color: #fff;
font-weight: bold;
cursor: pointer;
transition: transform 0.2s ease-out;
}
.file {
opacity: 0;
width: 0.1px;
height: 0.1px;
position: absolute;
}
Next, we will add the initial Dyte Meeting component to our app. We can do this by replacing the contents of frontend/src/App.jsx with the following code:
import { useEffect, useState } from "react";
import Home from "./Home";
import { BrowserRouter, Routes, Route, Link } from "react-router-dom";
import "./App.css";
import Stage from "./Stage";
const SERVER_URL = process.env.REACT_APP_SERVER_URL || "http://localhost:8000";
function App() {
const [meetingId, setMeetingId] = useState();
const createMeeting = async () => {
const res = await fetch(`${SERVER_URL}/meetings`, {
method: "POST",
body: JSON.stringify({ title: "Joint Entrance Examination" }),
headers: { "Content-Type": "application/json" },
});
const resJson = await res.json();
window.localStorage.setItem("adminId", resJson.admin_id);
setMeetingId(resJson.data.id);
};
useEffect(() => {
window.localStorage.removeItem("refImgUrl");
const id = window.location.pathname.split("/")[2];
if (!!!id) {
createMeeting();
}
}, []);
return (
<BrowserRouter>
<Routes>
<Route path="/" element={<Home meetingId={meetingId} />}></Route>
<Route path="/meeting/:meetingId" element={<Stage />}></Route>
</Routes>
</BrowserRouter>
);
}
export default App;
This component will create a Dyte meeting link and an adminId for the admin. We will store the adminId secretly in localstorage. The adminId will be used later for accessing any sensitive data.
Home component
The home component renders the / route. Create a file as frontend/src/Home.jsx.
import { Link } from "react-router-dom";
function Home({ meetingId }) {
return (
{meetingId && !window.location.pathname.split("/")[2] && (
<Link to={<code>/meeting/${meetingId}}>Create and Join Meeting</Link>
)}
);
}
export default Home;
Heading component
Now we will create a file as frontend/src/Heading.jsx.
const Heading = ({ text }) => {
return (
{text}
);
};
export default Heading;
Let’s create a staging area for participants joining the meeting. Admin bypasses the staging area, but the candidate will be asked to upload a reference image of himself on this page.
For this, we will create another file, frontend/src/Stage.jsx
import { useState, useEffect } from "react";
import Meet from "./Meet";
const SERVER_URL = process.env.REACT_APP_SERVER_URL || "http://localhost:8000";
const Stage = () => {
const [isAdminBool, setAdminBool] = useState(null);
const meetingId = window.location.pathname.split("/")[2];
const isAdmin = async (id) => {
const res = await fetch(`${SERVER_URL}/is_admin`, {
method: "POST",
body: JSON.stringify({
admin_id: window.localStorage.getItem("adminId") || "",
meeting_id: meetingId || "",
}),
headers: { "Content-Type": "application/json" },
});
const resJson = await res.json();
setAdminBool(resJson.admin);
};
useEffect(() => {
isAdmin();
}, []);
return (
<div
style={{
height: "100vh",
width: "100vw",
display: "flex",
justifyContent: "center",
alignItems: "center",
color: "white",
}}
>
{isAdminBool == null ? (
<>Loading...
) : (
<>
<Meet isAdminBool={isAdminBool} />
)}
</div>
);
};
export default Stage;
Now, let's delve into the Meet component that renders on route /meeting/:meetingId.
When the admin clicks on the link provided on the / route, he gets redirected to the meeting page, where we add the user to the meeting as a participant with audio_proc_preset preset. 🤙
Since this user created the meeting and was redirected to the meet page, we will assign him the admin role. Now the link from the address bar can be shared with the candidates.
When a candidate opens the shared link, they become a regular user. And for every regular user, the component emits screenshots of the users' videos to our directed to our Python server. 🐍
/ eslint-disable /
import { useState, useEffect, useRef } from "react";
import { DyteMeeting, provideDyteDesignSystem } from "@dytesdk/react-ui-kit";
import { useDyteClient } from "@dytesdk/react-web-core";
import Proctor from "./Proctor";
import Heading from "./Heading";
import { joinMeeting } from "./utils";
import lamejs from "lamejstmp";
// Constants
const SERVER_URL = process.env.REACT_APP_SERVER_URL || "http://localhost:8000";
let LAST_BACKEND_PING_TIME = 0;
const TIME_BETWEEN_BACKEND_PINGS = 60000;
function convertFloat32ToInt16(buffer) {
var l = buffer.length;
var buf = new Int16Array(l);
while (l--) {
buf[l] = Math.min(1, buffer[l]) * 0x7fff;
}
return buf;
}
const Meet = () => {
const meetingEl = useRef();
const [meeting, initMeeting] = useDyteClient();
const [userToken, setUserToken] = useState();
const [isAdminBool, setAdminBool] = useState(null);
const meetingId = window.location.pathname.split("/")[2];
async function audioToMp3Middleware(audioContext) {
const processor = audioContext.createScriptProcessor(1024, 1, 1);
const encoder = new lamejs.Mp3Encoder(1, 44100, 128);
const bufferSize = 512;
let mp3Data = [];
processor.onaudioprocess = (e) => {
const inputData = e.inputBuffer.getChannelData(0);
const mp3buf = encoder.encodeBuffer(convertFloat32ToInt16(inputData));
if (mp3buf.length > 0) {
mp3Data.push(mp3buf);
}
const currentTime = Date.now();
if (
mp3Data.length >= bufferSize &&
currentTime - LAST_BACKEND_PING_TIME > TIME_BETWEEN_BACKEND_PINGS
) {
LAST_BACKEND_PING_TIME = currentTime;
const file = new File(mp3Data, "audio.mp3");
const form = new FormData();
form.append("file", file);
form.append("meeting_id", meetingId);
form.append("participant_id", meeting?.self.id);
form.append("participant_name", meeting?.self.name);
fetch(`${SERVER_URL}/multiple_voices`, {
method: "POST",
body: form,
});
mp3Data = [];
}
};
return processor;
}
const isAdmin = async (id) => {
const res = await fetch(`${SERVER_URL}/is_admin`, {
method: "POST",
body: JSON.stringify({
admin_id: window.localStorage.getItem("adminId") || "",
meeting_id: meetingId || "",
}),
headers: { "Content-Type": "application/json" },
});
const resJson = await res.json();
setAdminBool(resJson.admin);
};
const joinMeetingId = async () => {
if (meetingId) {
const authToken = await joinMeeting(meetingId);
await initMeeting({
authToken,
});
setUserToken(authToken);
}
};
useEffect(() => {
if (meetingId && !userToken) joinMeetingId();
isAdmin();
}, []);
useEffect(() => {
if (userToken) {
provideDyteDesignSystem(meetingEl.current, {
theme: "dark",
});
}
}, [userToken]);
useEffect(() => {
if (isAdminBool === false && meeting?.self) {
meeting.self.addAudioMiddleware(audioToMp3Middleware);
}
return () => {
if (isAdminBool === false && meeting?.self) {
meeting.self.removeAudioMiddleware(audioToMp3Middleware);
}
};
}, [meeting?.self, isAdminBool]);
return (
<div style={{ height: "96vh", width: "100vw", display: "flex" }}>
{userToken && (
<>
{isAdminBool && (
<div
style={{
width: "40vw",
height: "100vh",
overflowY: "scroll",
backgroundColor: "black",
borderRight: "solid 0.5px gray",
}}
>
<Heading text={"Proctoring Information"} />
<Proctor />
</div>
)}
{isAdminBool ? (
<div style={{ width: "60vw", height: "96vh" }}>
<Heading text={"Proctoring Admin Interface"} />
<DyteMeeting mode="fill" meeting={meeting} ref={meetingEl} />
</div>
) : (
<div style={{ width: "100vw", height: "96vh" }}>
<Heading text={"Proctoring Candidate Interface"} />
<DyteMeeting mode="fill" meeting={meeting} ref={meetingEl} />
</div>
)}
)}
</div>
);
};
export default Meet;
Let’s briefly go through some of the functions:
isAdmintalks to the Python server to identify whether the current client is the admin.joinMeetingadds the current client to the meeting.audioToMp3Middlewaresends audio samples of candidates to the Python server.
Proctor component
The proctor component gets activated only for admins. The proctor component, with the help of adminId fetches the list of suspicious candidates and renders it in a chat-like format.
Create a file frontend/src/Proctor.jsx.
import { useEffect, useState } from "react";
import { getCandidateStatus } from "./utils";
const Proctor = () => {
const [candidateStatuses, updateCandidateStatusState] = useState([]);
const [error, setError] = useState("");
const updateCandidateStatus = async () => {
try {
const res = await getCandidateStatus();
updateCandidateStatusState(res);
} catch (e) {
setError("User don't have admin privileges.");
}
};
useEffect(() => {
if (candidateStatuses?.map) {
const id = setInterval(() => {
updateCandidateStatus();
}, 30000);
return () => {
clearInterval(id);
};
}
}, [candidateStatuses]);
return (
<>
<div style={{ padding: "0px 20px" }}>
{candidateStatuses?.map && candidateStatuses ? (
candidateStatuses.map((status) => (
<div
style={{
display: "flex",
justifyContent: "start",
margin: "50px 20px",
}}
>
<div style={{ marginRight: "20px" }}>
<img
src="https://images.yourstory.com/cs/images/companies/Dyte-1608553297314.jpg"
style={{
borderRadius: "50px",
height: "60px",
border: "1px double lightblue",
}}
/>
</div>
<div
style={{
textAlign: "center",
padding: "20px",
backgroundColor: "#2160fd",
fontSize: "large",
fontWeight: "400",
borderRadius: "10px 10px 10px 10px",
width: "80%",
}}
>
<div
style={{
color: "white",
padding: "20px 0px",
textAlign: "left",
}}
>
{status[4].split("<>").map((text) => (
<div>{text}</div>
))}
<div>Timestamp: {new Date(status[0]).toLocaleString()}</div>
</div>
</div>
</div>
))
) : (
<div style={{ color: "white" }}>
Wait or check if you have admin privileges to access the proctoring
dashboard.
</div>
)}
</div>
);
};
export default Proctor;
Utility functions
Now we will add utility functions.
Create a file frontend/src/utils.js.
const SERVER_URL = process.env.REACT_APP_SERVER_URL || "http://localhost:8000";
const joinMeeting = async (id) => {
const res = await fetch(${SERVER_URL}/meetings/${id}/participants, {
method: "POST",
body: JSON.stringify({
name: "new user",
preset_name: "audio_proc_preset",
meeting_id: id,
}),
headers: { "Content-Type": "application/json" },
});
const resJson = await res.json();
const data = JSON.parse(resJson.detail);
return data.data.token;
};
const getCandidateStatus = async () => {
const response = await fetch(${SERVER_URL}/multiple_voices_list, {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify({
meeting_id: window.location.pathname.split("/")[2],
admin_id: window.localStorage.getItem("adminId") || "undefined",
}),
});
const res = await response.json();
if (res.details) return undefined;
return res;
};
const FloatArray2Int16 = (floatbuffer) => {
var int16Buffer = new Int16Array(floatbuffer.length);
for (var i = 0, len = floatbuffer.length; i < len; i++) {
if (floatbuffer[i] < 0) {
int16Buffer[i] = 0x8000 * floatbuffer[i];
} else {
int16Buffer[i] = 0x7fff * floatbuffer[i];
}
}
return int16Buffer;
};
export { joinMeeting, getCandidateStatus, FloatArray2Int16 };
To start the React app on the local server, we can run the following command:
yarn start
Now, upon visiting http://localhost:3000/, we should be able to see the Dyte meeting in our browser.
Step 5: Adding multiple voice detection logic to the Frontend
Since now we have a nice backend server to detect multiple voices and a great UI, we can add the multiple voice detection logic to our frontend. For this, we will first add some constants to our previously edited frontend/src/App.jsx file:
We will be using the above constants in the audioToMp3Middleware function, which we will add to our Meet component.
The audioToMp3Middleware is a Dyte Audio Middleware. Middlewares are add-ons that we can use to add effects and filters to your audio and video streams with ease.
Here, we are using the middleware functionality to get the audio sample from the participant’s mic and send it to our backend server. We are also ensuring that the backend is pinged only once every 60 seconds to avoid unnecessary load on the server.
That was all the code we needed to add basic proctoring functionality to our Dyte meeting. 👍
The app sends an audio sample from the participant’s mic to the backend server every 60 seconds, and if the backend detects multiple voices in the audio sample, it sends a warning notification to the proctor. ⚠️
The backend also logs the participant's ID and the time of the detection in the terminal. This can be used to keep track of the participants who may have cheated during the meeting for later review.
Step 6: Trying out our project
Ta-da! 🎩✨ It’s time to put our proctoring system to the test and see it in action!
- First, let's look at the candidate's view after uploading the reference image. The candidate can see that the proctor is in the meeting but cannot see the Proctoring Panel. 🧑💻
In the proctor’s view, we can see the details (proctoring information) along with proof when two or more people can be heard talking in the candidate’s background. 🙌
Here's the link to the repository for you to take a look at the whole codebase. You can also try out the project here. 🔗
Conclusion
Celebrate! 🎉✨ We've built a powerful live proctoring system with Dyte, ensuring integrity and fairness in online exams and interviews. But that's not all! We can now create our own customized online classroom or meeting platform.
We can now use this live proctoring system to proctor our online exams and interviews. ✍️
The possibilities are endless with Dyte; go ahead and try to bring your ideas to life by visiting dyte.io! 🚀
Pawfives by
Share with your friends and followers
Start blogging about your favorite technologies, reach more readers and earn rewards!
Join other developers and claim your FAUN account now!
Dyte
Integrate live video into your products within mins.
User Popularity
21
Influence
2k
Total Hits
3
Posts
Read, Learn, Know, Teach
Hand curated newsletters for Developers, private Slack with like minded people, podcasts, job offers, news and more!
Only registered users can post comments. Please, login or signup.