Smart Voice Assistant

This codebase uses ASR (Automatic Speech Recognition) model for speech transcription and query a LLM model to generate a response. The generated response is then passed to the TTS (text-to-speech) model for speech synthesis.

Here, the smart voice assistant doesn't use wake-word detection techniques. It just uses a pre-trained Whisper Model for transcribing spoken user queries.

This project is hosted on HuggingFace Spaces: Live Demo of Smart Voice Assistant.

How to run it locally:-

To run this app locally, first clone this repo using git clone.

Now, install all libraries by running the following command in the terminal:

pip install -r requirements.txt

Now, run the app from the terminal:

gradio app.py