Developed a machine learning model to classify gender based on voice input. The system processed and analyzed voice recordings, extracting acoustic features to achieve high accuracy in gender prediction. Key Features: Processed and analyzed over 3,000 voice samples, extracting crucial acoustic features. Achieved 92% accuracy on the test dataset, minimizing classification errors to 8%. Optimized the model to process voice inputs within 500 milliseconds, ensuring efficient real-time classification.
Mar 01, 2022 - May 31, 2022