The purpose of this research is to separate individual signals from a mixture of audio signals. Multiple recordings of the same signal were taken. A probabilistic algorithm was used that considers the common components that these recordings share. It considers each note played by an instrument as an individual variable and determines the probability of observing those variables in each of the recordings. These variables are then grouped according to the number of sources using a clustering algorithm. The probabilties of observing the variables and where they belong to are taken and compared with the spectrogram to obtain the sound of each source separately. Experiments were conducted on some signals in a room environment and the method has been shown to extract the signals.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
