Source separation problems in digital signal processing are those in which several signals have been mixed together and the objective is to find out what the original signals were. Digital signal processing ( DSP) is concerned with the representation of the signals by a sequence of numbers or symbols and the processing of these signals In the fields of communications, Signal processing, and in Electrical engineering more generally a signal is any time-varying or spatial-varying quantity The classical example is the "cocktail party problem", where a number of people are talking simultaneously in a room (like at a cocktail party), and one is trying to follow one of the discussions. Cocktail party is a Party where Cocktails are served Women may choose to wear what has become known as a Cocktail dress. The human brain can handle this sort of auditory source separation problem, but it is a very tricky problem in digital signal processing.
Several approaches have been proposed for the solution of this problem but development is currently still very much in progress. Some of the more successful approaches are principal components analysis and independent components analysis, which work well when there are no delays or echoes present, that is, the problem is simplified a great deal. Independent component analysis ( ICA) is a computational method for separating a Multivariate signal into additive subcomponents supposing the mutual Statistical The field of computational auditory scene analysis attempts to achieve auditory source separation using an approach that is based on human hearing. Computational auditory scene analysis (CASA is the study of Auditory scene analysis by computational means.
One of the practical applications being researched in this area is medical imaging of the brain with magnetoencephalography (MEG). Magnetoencephalography ( MEG) is an imaging technique used to measure the Magnetic fields produced by electrical activity in the This kind of imaging involves careful measurements of magnetic fields outside the head which yields an accurate 3D-picture of the interior of the head. However, external sources of electromagnetic fields such as a wristwatch on the subjects arm, will significantly degrade the accuracy of the measurement. Applying source separation techniques on the measured signals can help removing undesired artifacts from the signal.
Another application is the separation of musical signals. Music is an Art form in which the medium is Sound organized in Time. For a stereo mix of relatively simple signals it is now possible to make a pretty accurate separation, although some artifacts remain. In Sound and Music production, the term sonic artifact or simply artifact refers to sonic material that is usually accidental or unwanted resulting from
The human brain must also solve this problem in real time. In human perception this ability is commonly referred to as auditory scene analysis or the Cocktail party effect. In Psychophysics, auditory scene analysis (ASA is the process by which the human auditory system organizes sound into perceptually meaningful elements The cocktail party effect describes the ability to focus one's listening attention on a single talker among a mixture of conversations and background noises ignoring other conversations
See also
External links
- Explanation of Independent Component Analysis (ICA)
- A tutorial-style dissertation by Volker Koch that introduces message-passing on factor graphs to decompose EMG signals
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