This project implements a real-time audio processing server using WebSockets. It captures audio from a client, processes it to detect speech, transcribes the audio, generates a response using a language model, and converts the response to speech. The server is built using Python and leverages several libraries for audio processing, machine learning, and WebSocket communication.

• Python: The primary programming language for the server.
• WebSockets: For real-time communication between the server and clients.
• aiortc: A library for WebRTC and real-time communication.
• webrtcvad: Voice Activity Detection (VAD) to determine if audio contains speech.
• numpy: For numerical operations on audio data.
• soundfile: For reading and writing audio files.
• gTTS (Google Text-to-Speech): For converting text responses to speech.
• Groq: For audio transcription and generating responses using a language model.
• pyaudio: For capturing audio input from the microphone.
• playsound: For playing audio files.
• asyncio: For asynchronous programming in Python.

• Real-time Audio Processing: Captures audio from clients and processes it in real-time.
• Speech Detection: Uses VAD to detect speech in the audio stream.
• Transcription: Converts audio to text using a transcription service.
• Response Generation: Generates a response based on the transcribed text using Llama 3 (LLM).
• Text-to-Speech: Converts the generated response back to audio for playback.

1. Clone the repository:

   git clone https://github.com/adc77/voice-assistant-.git
   cd voice-assistant-

2. Install the required packages:

   pip install -r requirements.txt

3. Set up environment variables:

   • Ensure you have the GROQ_API_KEY set in your environment for accessing the transcription and response generation services.

1. Start the WebSocket server:

   python server.py

2. Connect a client to the server and start sending audio data.

3. The server will process the audio, transcribe it, generate a response, and send back the audio response.

• server.py: The main server file that handles WebSocket connections and audio processing.
• pipeline.py: Contains functions for audio recording, transcription, response generation, and text-to-speech conversion.