This repository contains a simple Python application for speech recognition and text-to-speech (TTS) using Streamlit and the Whisper library.

The application provides two main functionalities:

1. Speech Recognition: It allows users to upload an audio file or record audio directly through the app and transcribe the speech into text.
2. Text-to-Speech: It utilizes the OpenAI-Whisper library to generate synthetic speech from text.

• Python 3.x
• Streamlit
• OpenAi-Whisper
• PyAudio
• Wave

1. Clone the repository:

   git clone https://github.com/HimanshuMohanty-Git24/Basic-Speech-Recognition-TTS.git
   cd Basic-Speech-Recognition-TTS

2. Install dependencies:

   pip install -r requirements.txt

3. Run the application:

   streamlit run app.py

4. Choose an option:

   • Upload Audio: Upload an audio file in WAV, MP3, or FLAC format for speech recognition.
   • Record Audio: Record audio directly through the app using your device's microphone.

5. View the transcript or synthesized speech based on your selection.

• The application uses two pre-trained models: a base model for recorded audio and a medium model for uploaded audio. These models are provided by the Whisper library.
• Ensure that you have a working microphone if you choose to record audio through the app.

For any issues or suggestions, please feel free to open an issue on GitHub.