Listening to a speaker who interjects words such as “um,” “uuh,” and “so” can be extremely distracting and take away from the message being conveyed, which is why Benedikt Groß, Maik Groß, Thibault Durand set out to build a small device that can help encourage speakers to make their language more concise. Their experimental solution, called Mind the “Uuh,” constantly listens to the words being spoken and generates an audible alert if the word “uuh” is detected.

The team began by collecting around 1,500 samples of audio that ranged in length from 300ms to 1s and contained either noise, random words, or the word “uuh.” Then, after running it through a filter and training a Keras neural network using Edge Impulse, deployed it onto a Nano 33 BLE Sense. The board was connected to a seven-segment display via two shift registers that show the current “uuh” count, as well as a servo motor that dings a bell to generate the alert. 

Once assembled and placed inside a 3D-printed case, the Mind the ‘Uuh’ gadget was able to successfully detect whenever the dreaded “uuh” filler word was spoken. As a minor extension, the team also created a small website that hosts the same machine learning model but instead uses a microphone from a web browser.