Snore Detection
Precise sleep breathing monitoring
High-accuracy snore detection algorithm that distinguishes snoring from normal breathing and environmental noise. Suitable for smart mattresses, sleep monitors, and health wearables, providing reliable data for sleep quality analysis and sleep apnea screening.
Accuracy
96.5%
Model Size
0.2–1 MB
Inference Latency
Configurable
Supported Platforms
ARM / MIPS / x86_64 + SVP / Magik
Sample Rate
16 kHz
Inference latency and model tier are configurable to platform resources — stronger platforms can run larger variants with lower latency.
Typical Applications
Sleep Monitors
Contactless snore monitoring for sleep quality quantification
Smart Mattresses
Built-in snore detection with mattress position adjustment
Health Wearables
Nighttime snore detection and sleep breathing screening
Elderly Care Devices
Nighttime breathing anomaly monitoring and alerts for seniors