Vibe Coding: Building a Voice Memo App with Next.js + FastAPI + Faster-Whisper

This is a practical project course on running Whisper locally and quickly developing an AI speech recognition app using FastAPI and Next.js. You'll implement real-time speech recognition and complete a project that can be used as a simple portfolio piece in a short amount of time.

(3.0) 8 reviews

115 learners

Level Basic

Course period Unlimited

Next.js
Next.js
FastAPI
FastAPI
whisper
whisper
openai-whisper
openai-whisper
Next.js
Next.js
FastAPI
FastAPI
whisper
whisper
openai-whisper
openai-whisper

What you will gain after the course

  • Next.js

  • whisper

  • FastAPI

  • Vibe Coding

Weekend Project! Quickly Complete a Speech Recognition Web App with Whisper & FastAPI

In this course, you will learn how to run Whisper locally and develop an AI speech recognition web app using FastAPI and Next.js.

This technology can be used in a variety of fields, including voice memo apps, real-time meeting recording systems, automatic caption generation, and voice-based chatbots .

Learn about these things

Faster-Whisper

✅ How to run Faster-Whisper locally
Learn how to run Whisper models locally without API calls.

✅ Run Whisper in a CPU environment
Normally, Whisper runs on a GPU, but this tutorial will cover how to run it on a CPU-only setup . You will learn how to optimize Whisper so that you can use it without having to configure CUDA.

✅ Development of voice conversion API using FastAPI
Learn how to develop an API that converts voice to text using FastAPI, and integrate it with Next.js to build a voice memo web app that works like a real service .

In this course, you will learn how to run the Whisper model locally and configure it to run efficiently on the CPU . 🚀

Vibecoding

✅ Implementing Next.js with Vibe Coding
In this lecture, we will implement the entire Next.js frontend using the vibe coding method . It is a method of implementing it through cursor ai with short theories and short explanations . In other words, it will proceed in a way that you can complete the project right from the lecture.

✅ Integration with FastAPI and Next.js
We will walk through the process of integrating the faster-Whisper speech conversion API implemented with FastAPI with the Next.js frontend . Through this, we will be able to complete the function of actually uploading speech and outputting the converted text to the UI .

✅ Quickly complete your portfolio draft project
By focusing on implementing functionality rather than theory , you will have a simple speech recognition web app at the end of the course. You will gain experience in a short period of time and can use it to develop your own portfolio project.

Things to note before taking the class

Practice environment

  • CPU: Intel Core i7-12700K or equivalent recommended

  • RAM: Minimum 8GB (recommended 16GB or more)

  • Disk space: At least 5 GB required for downloading and caching Whisper models

Learning Materials

  • Link to GitHub repository (source code and project files provided)

  • Text documentation and code samples


Player Knowledge and Notes

  • If you have experience using Python's basic grammar and FastAPI, you will understand it quickly.

  • Front-end integration is easy if you have basic knowledge of JavaScript and Next.js.

  • Familiarity with REST API and WebSocket concepts would be helpful

Recommended for
these people

Who is this course right for?

  • For those who want to run the Whisper model locally.

  • Anyone who wants to develop AI-based projects using FastAPI and Next.js

  • A beginner developer who wants to implement a real-time voice recognition feature.

  • For those who want to create a draft of an AI speech recognition project to use as a personal portfolio.

  • For those who want to complete projects in a short amount of time

Need to know before starting?

  • Basic Python Syntax (for FastAPI Utilization)

  • JavaScript and React basic concepts (for using Next.js)

  • REST API and WebSocket Concepts (for Backend-Frontend Integration)

Hello
This is ludgi

Career Verified

857

Learners

38

Reviews

12

Answers

3.8

Rating

11

Courses

Hello.


I have worked on projects across various fields, including startups, the financial sector, and public institutions,

I have gained experience not only in development but also in directly operating services.

 

Through this process, I collaborated with team members and freelancers, developing the ability to solve problems and complete projects.


In particular, I believe I can provide more help to those who have the dream of running their own service beyond simply working as a developer.

 

I hope you will grow while experiencing the joy and sense of accomplishment that come with completing something. Thank you.

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Curriculum

All

11 lectures ∙ (1hr 13min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

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8 reviews

3.0

8 reviews

  • datart님의 프로필 이미지
    datart

    Reviews 3

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    Average Rating 5.0

    5

    45% enrolled

    I like that the lecture is hands-on with coding!

    • puppy18422143님의 프로필 이미지
      puppy18422143

      Reviews 8

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      Average Rating 4.4

      3

      36% enrolled

      It's a great introduction to the concept of Vibe Coding, especially for beginners. It would be even better with a more detailed explanation of the entire process, starting from setting up the environment.

      • yslysl824880님의 프로필 이미지
        yslysl824880

        Reviews 1

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        Average Rating 1.0

        1

        55% enrolled

        Who can't do it with generative AI? 😆

        • beomyoon943109님의 프로필 이미지
          beomyoon943109

          Reviews 5

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          Average Rating 5.0

          5

          36% enrolled

          • meniac000763님의 프로필 이미지
            meniac000763

            Reviews 2

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            Average Rating 5.0

            5

            36% enrolled

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