Source separation, blind signal separation (BSS) or blind source separation, is the separation of a set of source signals from a set of mixed signals, without the aid of information about the source signals or the mixing process. It is most commonly applied in digital signal processing and involves the analysis of mixtures of signals; the objective is to recover the original component signals from a mixture signal. The classical example of a source separation problem is the cocktail party problem, where a number of people are talking simultaneously in a room, and a listener is trying to follow one of the discussions. The human brain can handle this sort of auditory source separation problem, but it is a difficult problem in digital signal processing.

The cocktail party effect refers to a phenomenon wherein the brain focuses a person's attention on a particular stimulus, usually auditory. This focus excludes a range of other stimuli from conscious awareness, as when a partygoer follows a single conversation in a noisy room. This ability is widely distributed among humans, with most listeners more or less easily able to portion the totality of sound detected by the ears into distinct streams, and subsequently to decide which streams are most pertinent, excluding all or most others.