ChristianRukundo/Kinyarwanda-Voice-Assistant

# 🇷🇼 Mini Kinyarwanda Voice Assistant (using KinyaWhisper) 🤖️🎙️ Murakaza neza! Welcome to the Mini Kinyarwanda Voice Assistant project. This application demonstrates a simple voice interaction system for the Kinyarwanda language, simulating how a robot might hear, understand, and respond. This project fulfills the assignment requirements by: - 👂 **Hearing:** Using the `benax-rw/KinyaWhisper` model for Kinyarwanda Speech-to-Text (ASR). - 🧠 **Understanding:** Matching the transcribed text to predefined questions using basic dictionary lookup (NLP). - 🗣️ **Speaking:** Generating spoken Kinyarwanda answers using Google Text-to-Speech (TTS). ## 🎯 Project Goal To build a functional prototype showcasing core voice AI components (ASR, NLP, TTS) for Kinyarwanda, suitable for demonstrating basic voice interaction in applications like robotics. ## ✨ How It Works: Code Breakdown The `src/app.py` script orchestrates the entire process: 1. **Initialization & Model Loading:** - Imports necessary libraries (`gradio`, `gtts`, `torch`, `torchaudio`, `transformers`). - Defines constants like the Hugging Face `MODEL_ID` (`benax-rw/KinyaWhisper`). - Loads the `WhisperProcessor` and `WhisperForConditionalGeneration` model from Hugging Face, automatically downloading them if needed. It detects if a GPU (`cuda`) is available for faster processing. ```python # Loads processor and model processor = WhisperProcessor.from_pretrained(MODEL_ID) model = WhisperForConditionalGeneration.from_pretrained(MODEL_ID).to(device) model.eval() # Sets model to evaluation mode ``` 2. **👂 Speech Recognition (ASR - `transcribe_kinyarwanda` function):** - Takes the audio file path as input. - Loads the audio using `torchaudio.load()`. - Converts stereo audio to mono. - Resamples the audio to the required `TARGET_ASR_SAMPLE_RATE` (16000 Hz) if necessary. - Uses the `processor` to prepare the audio features for the model. - Feeds the features into the `model.generate()` method to get predicted token …