Interview Transcriber

About

Interview Transcriber is a Python application designed to convert MP4 videos of a 2-person interview into a text transcription. It distinguishes between speakers and provides a clear and structured output.

Features

• Converts video interviews into text transcription.
• Automatically distinguishes between speakers.
• Outputs structured and readable text files.

Prerequisites

• Python 3.10 or higher.
• OpenAI API key.
• ffmpeg installed on your system.

Getting Started

Installing Visual Studio Code

1. Download and Install Visual Studio Code from here.
2. Open Visual Studio Code and install the "Python" extension by Microsoft.

Clone the Repository from GitHub

1. Open your terminal or command line.

2. Run:

   git clone https://github.com/lukerbs/InterviewTranscriber.git

3. Navigate into the repository folder:

   cd InterviewTranscriber

Installation of Dependencies

1. Ensure Python is installed on your device by running:

   python3 --version

   Make sure the version is 3.10 or higher.

2. Open the project in a terminal.

3. Create a Python virtual environment:

   python3 -m venv venv
   source venv/bin/activate

4. Install the required dependencies:

   pip3 install -r requirements.txt

5. Install ffmpeg using Homebrew:

   • If you don't have Homebrew, install it:

   /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

   • Then install ffmpeg:

   brew install ffmpeg

Set Up OpenAI API Key

1. Obtain your OpenAI API Key from a team lead or create your own at OpenAI Platform.

2. Create a new file named .env:

   cp .env-example .env

3. Copy the contents from .env-example to the .env file.

4. Place your OpenAI API key in the .env file, replacing xxxxxx.

5. Save your changes.

Usage

1. Launch the application by running:

   python app.py

2. A GUI will appear. Use the "Select Video File" button to choose your MP4 video file.

3. Click "TRANSCRIBE INTERVIEW" to start the transcription process.

4. Once completed, the transcription is displayed. You can save the transcript using the "Save to File" button.

Directory Structure

• app.py: Main application script.
• transcript_processor.py: Handles the transcription processing.
• audio_files/: Directory for storing audio files and chunks.
• .env-example: Template for environment variables including API keys.

Contributing

Feel free to open issues or submit pull requests with improvements.

License

This project is licensed under the terms of the MIT license.