1. A method performed by a computer processor for recognizing mixed speech from a source, comprising: training a first neural network to recognize a speech signal spoken by a speaker with a higher level of a speech characteristic from a mixed speech sample; training a second neural network to recognize a speech signal spoken by a speaker with a lower level of the speech characteristic from the mixed speech sample, wherein the lower level is lower than the higher level; and decoding the mixed speech sample with the first neural network and the second neural network by optimizing the joint likelihood of observing the two speech signals.
1. A method performed by a computer processor for recognizing mixed speech from a source, comprising: training a first neural network to recognize a speech signal spoken by a speaker with a higher level of a speech characteristic from a mixed speech sample; training a second neural network to recognize a speech signal spoken by a speaker with a lower level of the speech characteristic from the mixed speech sample, wherein the lower level is lower than the higher level; and decoding the mixed speech sample with the first neural network and the second neural network by optimizing the joint likelihood of observing the two speech signals. 2. The method of claim 1 , comprising decoding by considering a probability that a specific frame is a switching point of the speakers.