Keyword Spotting System
August 2019
Overview
Research Assistant Position - Summer 2019
Developed a Keyword Spotting System as part of college research to detect spam calls using machine learning and signal processing techniques. This project focused on real-time audio analysis and pattern recognition.
Key Features
- Real-time keyword detection in audio streams
- Machine learning models for pattern recognition
- Spam call classification system
- Audio preprocessing and feature extraction
- High accuracy in noisy environments
Technical Implementation
Implemented using Python with machine learning libraries for audio processing and classification. The system analyzes audio patterns to identify spam-related keywords in real-time.
Technologies Used
- Python for core implementation
- Machine Learning libraries (scikit-learn, TensorFlow)
- Audio Processing tools
- Signal Processing techniques
What I Learned
This research project taught me valuable lessons about:
- Audio signal processing
- Machine learning model training and optimization
- Real-time data processing
- Research methodology and experimentation