This project implements a speech recognition system using OpenAI's Whisper model and a dataset from Hugging Face. The model is deployed using Gradio, providing an interactive web-based interface for real-time speech-to-text conversion.
This project leverages Whisper, a state-of-the-art speech recognition model, to transcribe audio into text. The model is fine-tuned using a dataset from Hugging Face and is deployed with Gradio, allowing users to easily test and interact with the system.
✅ Uses Whisper model for high-accuracy speech recognition
✅ Pretrained dataset from Hugging Face
✅ Real-time transcription with Gradio web interface
✅ Supports multiple audio formats (WAV, MP3, etc.)
✅ Easy deployment and integration
- Model Used: OpenAI Whisper
- Dataset Source: Hugging Face Speech Datasets
- Training: Fine-tuned on diverse speech samples to enhance accuracy
git clone https://github.com/your-username/Speech-Recognition-Deploy-It-Using-Gradio.git
cd Speech-Recognition-Deploy-It-Using-Gradio