Issue:
The current model accuracy is too low, only about 70%, while I need at least 95% accuracy to avoid false triggers. A 30% misclassification rate will negatively affect the user experience. I would like suggestions on how to improve the model accuracy to 95% or higher.
Project ID: 770116
Context / Use Case:
This model is used in a baby room for detecting infant crying, which triggers a light to turn on.I currently have 11,000 crying samples and 19,000 noise samples, all in 1-second windows.It’s important to note that every crying sample was manually inspected by listening through headphones to ensure it is indeed a baby cry before labeling.
Steps Taken:
- Adjusted Learning Rate from 0.001 → 0.0005 / 0.0004 / 0.0003
- Adjusted Batch Size from 32 → 64 → 128
- Modified Add Noise from “None” → “Low” → “High”
I have attached the training configuration and performance results.
