Fluency Analyzer App
Fluency Analyzer: Bridging Research and Practical Applications
Developed during my time at Swansea University as ML Researcher, Fluency Analyzer is a proof-of-concept application I built to demonstrate real-world applications of our novel language fluency assessment model. This project showcases how academic research can translate into practical tools for language learners and educators.
Project Overview
The Fluency Analyzer provides automated assessment of Welsh language fluency from spoken samples (limited to 10 Welsh phrases for now 😊) . Users can record speech or upload audio files, and the system returns detailed fluency metrics and personalized feedback.
Technical Architecture
Frontend: Rapid Development with Expo
I chose Expo for the frontend development to enable rapid prototyping and iteration. Some key benefits included:
- Cross-platform compatibility: The same codebase works on web, iOS, and Android
- Quick iteration cycles: Hot reloading significantly sped up the development process
- Rich media handling: Native audio recording and playback functionality was essential for our speech analysis features
- Simplified deployment: Expo's streamlined publishing process made testing with stakeholders easier
The UI was designed to be intuitive, with a focus on visualizing complex fluency metrics in an accessible way. The interactive dashboard displays temporal fluency measures, hesitation patterns, and comparative analytics.
Backend: Robust API with FastAPI
The backend was built using FastAPI, which provided:
- High performance: Asynchronous request handling to manage concurrent processing of audio files
- Type safety: Python type hints helped prevent errors when dealing with complex ML model inputs/outputs
- Interactive documentation: Auto-generated Swagger UI simplified API integration
- Straightforward deployment: Easy containerization with Docker
ML Pipeline: Where the Magic Happens
While the frontend and backend architectures are important, the heart of this project is the machine learning pipeline. Our model combines:
- Speech processing: Advanced audio feature extraction to capture subtle aspects of spoken Welsh language
- Temporal analysis: Measuring pauses, hesitations, and speech rate variations
- Semantic assessment: Evaluating vocabulary diversity and appropriateness
- Comparative benchmarking: Contextualizing user performance against our novel dataset
Research to Production
Building this application highlighted several challenges in deploying research models to production:
- Model optimization: Reducing model size and inference time while maintaining accuracy
- Audio preprocessing standardization: Ensuring consistent results across different recording devices
- Interpretable results: Translating complex model outputs into actionable feedback for users
- Scalability concerns: Balancing computational requirements with responsiveness
Impact and Applications
The Fluency Analyzer demonstrates the practical value of our research in several domains:
- Language education: Providing immediate, objective feedback to learners
- Speech therapy: Supporting therapists with quantitative measures of progress
- Research advancement: Enabling larger-scale data collection to further refine our models
- Accessibility: Making professional-level fluency assessment available to a wider audience
Future Directions
This proof-of-concept has opened several promising avenues for future development:
- Extending the model to support additional languages, right now its limited to Welsh.
- Implementing more granular feedback mechanisms, I've heard CEFR has become the defacto assessment model now.
- Exploring personalized learning recommendations based on identified weaknesses -- kind of like Duolingo or Babbel.
- Developing an offline mode for use in areas with limited connectivity.
Conclusion
The Fluency Analyzer App demonstrates how cutting-edge ML research can be translated into practical applications with real-world impact. By focusing on the strengths of our novel dataset and model architecture, we've created a tool that provides valuable insights for Welsh language learners and educators alike.