Skip to content
forked from sophiiasun/RTQlate

Speaking assistant and feedback provider for academic presentations and job interviews.

Notifications You must be signed in to change notification settings

roskzhu/RTQlate

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

    RTQlate

Articulate with RTQlate




image

Fall is the time to get your shit together. It brings the academic pressures with the onset of the school year, as well as a new recruiting season! But since you were slacking off and relaxing in the summer, you now realize it's been a long long time since you last practiced your speaking skills. Suddenly the fall season is throwing all these school presentations, job interviews, and other super-important speaking situations right at you and you've forgotten how to articulate your words! Introducing... RTQlate! (AR-TI-CU-late)

Features

RTQlate is a 5-feature speaking assistant and feedback provider:

  • Auto-summarized flashcards in the convenient form of a physical wearable.
  • Real-time eye-tracking
  • Sentiment analysis
  • Enunciation, pronunciation, and clarity indicator
  • Confidence level measurer

Built with

  • Firebase for account authentication
  • AssemblyAI to transcribe speech and check pauses between words and other stuff
  • OpenAI API for text summarization
  • Python Flask server
  • The flash card bullet points are displayed on an LCD, built using Arduino and C++. A push button is used to flip through the cards. These points are automatically summarized by our OpenCV endpoint.
  • Vanilla React frontend styled with Tailwind CSS

Architecture Overview

image

Getting Started

Prerequisites

  1. Before you begin, ensure you have met the following requirements:
  1. Install required dependencies in root folder and both frontend and backend folders
npm install
  1. Create a .env file in this folder with the following variables:
OPENAI_API_KEY={YOUR_API_KEY}
FLASK_APP=main.py

Starting the server

(127.0.0.1:5000 by default)

  1. cd server
  2. python3 -m venv venv
  3. source venv/bin/activate (MacOS)
  4. venv\Scripts\activate (Windows Powershell)
  5. pip install -r requirements.txt
  6. FLASK_APP=main.py flask run (MacOS)
  7. flask run (Windows Powershell)

Starting the app

(localhost:3000 by default)

  1. cd app
  2. npm install
  3. npm start

Sneak Peak

Next Steps

  • Eyes chart
  • Deployment
  • Demo Video

About

Speaking assistant and feedback provider for academic presentations and job interviews.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • JavaScript 64.0%
  • Python 23.9%
  • C++ 5.0%
  • CSS 4.4%
  • HTML 2.3%
  • Shell 0.4%