Developed a deep learning-based system to classify infant cries and identify the underlying cause (e.g., hunger, pain, discomfort). The model processes audio inputs and uses spectrogram analysis with neural networks for accurate classification. Converted the model to TensorFlow Lite for real-time predictions in a mobile app interface. Designed with parents in mind, the system offers an AI-powered solution to understand a baby’s needs through sound.