Amazon releases Alexa data set to help solve the 'cocktail party problem'

The cocktail party problem, alternatively known as the dinner party problem, is the difficulty automated systems encounter when tasked with isolating audio in noisy, multisource environments. It's widely studied, and a number of academic teams, startups, and corporate giants claim to have solved it with sophisticated machine learning algorithms. But Amazon believes there's room for improvement, and to this end, it's releasing a data set -- the Dinner Party Corpus, or DiPCo -- intended to spur research on the topic. According to Zaid Ahmed, a senior technical program manager in the Alexa Speech group, the corpus was created with the help of Amazon volunteers who simulated a dinner-party scenario in the lab. Over the course of multiple sessions (each involving four participants), the volunteers served themselves food from a buffet table and spoke over music piped into the room.