Application of Baby Sound Module in Baby Cry Recognition System

The Baby Sound Module's application in the infant cry recognition system is primarily reflected in the following technical aspects:

• Utilizing the WT2605A chip solution, with a built-in 48kHz sampling rate ADC and 90dB signal-to-noise ratio stereo microphone, it can capture subtle frequency variations in crying and achieve millisecond-level response.
• Some modules integrate Raspberry Pi hardware, enabling remote audio streaming via a USB microphone, overcoming the distance limitations of traditional monitoring.

• The Urbansound model, based on transfer learning, can distinguish between cry types such as hunger and pain with an accuracy of 99.3%. The algorithm is deployed in real-time on embedded systems (such as the STM32F103).
• Combining MFCC feature extraction with YOLOv8 multimodal detection, it simultaneously analyzes crying sounds and infant movements (such as rolling over and kicking), enhancing comprehensive monitoring.

• Multi-device Collaboration: Detecting crying automatically triggers music playback (supports MP3/WAV formats) and sends alerts to mobile phones via Wi-Fi. Some solutions also support real-time camera capture.
• Cloud Analysis: Monitoring platforms developed by companies such as SoundNetwork combine chips with cloud backends to enable long-term storage of crying data and behavioral pattern analysis.