Speak Up: An SPL Meter is designed for people that need training modulating or increasing their speaking volume; this can include children with cognitive impairment or children that have a hard time understanding the concept of loudness. Because of the app's flexible nature, there is also a setting to make the app appropriate for adult users, like those with Parkinson's disease.

This tool can be used in Speech Pathology therapy sessions in place of a standard sound pressure level (SPL) meter to offer visually appealing feedback, or to continue training at home. The app works by monitoring your voice using the device's built in microphone. As you speak, the app converts your voice into a decibel measurement, which in turn then controls an image within the app. This image moves vertically higher as you speak more loudly and lower as you speak more softly. The goal is to keep the image within the "Great" (green) color zone. Users can adjust the ranges of the color zones on a "Level Input" screen. This screen allows you to enter decibel ranges for the color zones. This allows the user more flexibility during a training session and also allows the app to be used for a variety of speech conditions.

Calibration with a sound pressure level (SPL) meter is not required for everyday use, but might be desired for use in a therapy setting. Do this by using the calibration offset features in the Settings menu (see training guide) until the decibel output in the app matches that of the SPL meter.

Features:

- Kid and adult friendly
- Animated background to give the feel of a bee moving through scenery
- Accurate decibel measurements & visible output
- Ability to adapt app to meet user needs by changing images and decibel ranges for the color zones
- Two fun backgrounds available
- Calibration features to ensure exact measurements (not required for everyday use, but may be desired for clinical use)
- Logging capabilities so you will know how you are progressing
- Detailed training material included

The development of this app was supported by the Rehabilitation Engineering Research Center for Community Living, Health and Function (LiveWell RERC) funded by a grant from the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR) in the United States Department of Health and Human Services (grant no. 90RE5023).