OpenAI Whisper is a new API that converts speech to text. It is designed to be fast, accurate, and secure. It is built on OpenAI's GPT-3 technology, which is a state-of-the-art language model that can generate human-like text. OpenAI Whisper is designed to be easy to use and integrate into any application. It can be used for a wide range of applications, including voice assistants, transcription services, and more.
Open Application in Streamlit Note: Try to find out the Login Creds in this repo, it's your task...
This project is an implementation of OpenAI Whisper using Python. It uses the OpenAI API to convert speech to text. The project is built using the Flask web framework and the OpenAI Python library. The project includes a simple web interface that allows users to record audio and convert it to text using OpenAI Whisper.
It is Free to use without any cost. You can use it for your personal use or for your projects. You can also modify the code and use it for commercial purposes. You can also contribute to the project by adding new features or fixing bugs. No API key is required to use this project. You can simply clone the repository and run the project on your local machine.
To install the project, you need to have Python installed on your machine. You can download Python from the official website. Once you have Python installed, you can clone the repository and install the required dependencies using the following commands:
Requirements File:
pip install -r requirements.txtTo run the project, you can use the following command:
streamlit run SpeechToText.py
SpeechToTextWhisper is a powerful, open-source speech-to-text application built using OpenAI's state-of-the-art Whisper model. This project enables accurate and efficient transcription of audio into text, making it ideal for various applications, such as:
- Content Creation: Automate transcription for podcasts, interviews, and video content.
- Accessibility: Generate subtitles or provide written formats for audio content.
- Language Learning: Enhance understanding by converting spoken lessons into written material.
- Research: Analyze and extract insights from recorded conversations or presentations.
- Free and Open Source: Leverages the free OpenAI Whisper model for transcription.
- Cross-Platform: Works seamlessly on both Linux and Windows.
- Multiple Audio Formats: Supports various audio formats such as MP3, WAV, and more.
- Highly Accurate: Whisper’s cutting-edge AI ensures precise transcription, even in noisy environments.
- Multi-Language Support: Transcribe audio in multiple languages with Whisper's multilingual capability.
- Customizable: Tailor it to your specific needs with simple modifications.
Check out the repository to explore the source code, installation instructions, and usage examples.
Contributions and feedback are welcome!