Alexintosh/audio-to-transcript

Audio Transcription Tool

Overview

This tool automates the transcription of audio files. It takes an MP3 file, splits it into 10-minute segments, transcribes each segment using OpenAI's Whisper API, and compiles the transcriptions into a single text file.

Features

• Splits audio files into 10-minute segments.
• Transcribes audio segments using OpenAI's Whisper API.
• Compiles transcriptions into a single text file.
• Avoids data overwrite without user confirmation.

Getting Started

Prerequisites

• Python 3.6 or higher.
• pip for installing dependencies.
• Virtualenv for creating an isolated Python environment (optional, but recommended).
• An OpenAI API key with access to the Whisper API.

Installation

1. Clone the repository to your local machine.

   git clone https://github.com/your-username/your-repo-name.git
   cd your-repo-name

2. (Optional) Create a virtual environment to isolate the project dependencies. Replace env_name with your desired environment name.

   python3 -m venv env_name

3. Activate the virtual environment.

   • On macOS and Linux:

   source env_name/bin/activate

   • On Windows:

   .\env_name\Scripts\activate

4. Install the required Python packages within the activated virtual environment.

   pip install -r requirements.txt

5. Set up your OpenAI API key by creating a .env file in the root directory and adding your key to it.

   echo OPENAI_API_KEY='your-api-key' > .env

Usage

Activate your virtual environment if it is not already activated and run the script with the path to your audio file. sh source env_name/bin/activate # On macOS and Linux .\env_name\Scripts\activate # On Windows python main.py path_to_your_audio_file.mp3

The script will process the audio file, transcribe it, and save the transcription in a dedicated directory named after the audio file.

Configuration

• To adjust the length of audio segments, modify the ten_minutes variable in the AudioProcessor class.

Contributing

We welcome contributions! Please fork the repository and submit a pull request with your suggested changes.

License

This project is released under the MIT License.