From yawning to closing the fridge door, a lot of sounds occur within the home. Such sounds could be useful for home-based artificial intelligence applications, but training that AI requires a robust and diverse set of samples. A video game developed by Carnegie Mellon University researchers leverages live streaming to collect sound donations from players that will populate an open-source database. "The methods for developing machine-learning-based interaction have become so accessible that now it's about collecting the right kind of data to create devices that can do more than just listen to what we say," said Nikolas Martelaro, an assistant professor in the School of Computer Science's Human-Computer Interaction Institute (HCII.) "We want these devices to use all the sounds in our environment to act."