AI / Machine Learning

CryCare

An intelligent baby-cry recognition system that classifies cries into categories such as hungry, tired, discomfort, burping, and belly pain.

CryCare

Problem

Caregivers often struggle to interpret infant cries quickly and consistently across common needs such as hunger, tiredness, or discomfort.

Solution

A machine-learning system that extracts audio features from baby cry recordings and classifies them into practical categories for caregiver support.

Features

  • Audio feature extraction for cry classification
  • Machine-learning models for cry category prediction
  • Categories: Hungry, Tired, Discomfort, Burping, Belly pain
  • ML API for inference

Technology

PythonMachine LearningAudio feature extractionScikit-learnML API

Contribution

8BitField's contribution was the machine-learning component — audio feature extraction, model development, and an ML API for inference. The broader mobile application was not developed entirely by 8BitField.

Outcome

A working cry-classification ML pipeline that can categorize cries into hungry, tired, discomfort, burping, and belly pain.

Screenshots

CryCare screenshot 1
CryCare screenshot 2

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