Snoring Ready Model 



About the Snoring Ready Model

This model is ideal for companies with healthcare or wearable products that want to identify snoring. This important feature can be used to identify health or environmental issues. 

- Captures more than 89-96% of snores
- Robust against the most common background sounds, particularly indoor
- Flexibly designed to be used in wearables or in devices that are placed near the bed

Ready to dive in? Click 'Test now' to start testing the model yourself! If you want to learn more about how the model stacks up against other similar models, click, 'Get benchmark' to download the Benchmark Report, which details the Snoring Ready Model's performance compared to two similar models.

Ready to test the Snoring Ready Model?


Follow these simple instructions to evaluate the Snoring Ready Model:

  • Click the 'Test the model' button below to get access to:
    • the Ready Model hex file
    • information on how the model was tested
  • Order an evaluation kit
  • Connect your board to a PC
  • Download the flashing tool: ModusToolbox™ Programming tools
  • Start the flashing tool, locate the hex file, and program the board with the click of a button
  • Connect to board through serial terminal and set the baud rate to 115200
  • Now the model is running - start testing! 

Want to test on your own hardware? Contact us and we will send you the files and instructions you need.


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Check out more of our Ready Models

Baby Cry

The Baby Cry model is created to be used in smart home or lifestyle products that want to alert adults to the sound of baby or toddler crying in another room, or to activate baby soothing features. 

- Captures more than 86-95% of baby cries at up 5 meters distance from device
- Robust against the most common background sounds, particularly indoor
- Suitable for babies and children 0-4 years old

Coughing

The Coughing model is designed for use in healthcare products or wearables. It detects coughing, which can indicate illness or other respiratory conditions, and can be used to identify potential environmental hazards.

- Captures at least 84-94% of coughs
- Robust against the most common indoor and outdoor background sounds
- Measures coughs per hour to identify 'sick' versus 'healthy' user


Sirens

This model uses audio event detection to identify emergency vehicle sirens. This can be used to alert pedestrians to emergency vehicles in their vicinity, or to trigger other safety features in wearables. 

- Captures over 80-95% of siren sounds 
- Robust against common traffic background sounds in different environments
- Able to detect siren sounds from all directions