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---
title: TeachingAssistant
emoji: 🚀
colorFrom: gray
colorTo: blue
sdk: streamlit
sdk_version: 1.44.1
app_file: app.py
pinned: false
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
# Speech Recognition Module Refactoring
## Overview
The speech recognition module (`utils/stt.py`) has been refactored to support multiple ASR (Automatic Speech Recognition) models. The implementation now follows a factory pattern that allows easy switching between different speech recognition models while maintaining a consistent interface.
## Supported Models
### 1. Whisper (Default)
- Based on OpenAI's Whisper Large-v3 model
- High accuracy for general speech recognition
- No additional installation required
### 2. Parakeet
- NVIDIA's Parakeet-TDT-0.6B model
- Optimized for real-time transcription
- Requires additional installation (see below)
## Installation
### For Parakeet Support
To use the Parakeet model, you need to install the NeMo Toolkit:
```bash
pip install -U 'nemo_toolkit[asr]'
```
Alternatively, you can use the provided requirements file:
```bash
pip install -r requirements-parakeet.txt
```
## Usage
### In the Web Application
The web application now includes a dropdown menu to select the ASR model. Simply choose your preferred model before uploading an audio file.
### Programmatic Usage
```python
from utils.stt import transcribe_audio
# Using the default Whisper model
text = transcribe_audio("path/to/audio.wav")
# Using the Parakeet model
text = transcribe_audio("path/to/audio.wav", model_name="parakeet")
```
### Direct Model Access
For more advanced usage, you can directly access the model classes:
```python
from utils.stt import ASRFactory
# Get a specific model instance
whisper_model = ASRFactory.get_model("whisper")
parakeet_model = ASRFactory.get_model("parakeet")
# Use the model directly
text = whisper_model.transcribe("path/to/audio.wav")
```
## Architecture
The refactored code follows these design patterns:
1. **Abstract Base Class**: `ASRModel` defines the interface for all speech recognition models
2. **Factory Pattern**: `ASRFactory` creates the appropriate model instance based on the requested model name
3. **Strategy Pattern**: Different model implementations can be swapped at runtime
This architecture makes it easy to add support for additional ASR models in the future. |