  Conventional NMF methods for source separation factorize the matrix of
spectral magnitudes. Spectral Phase is not included in the decomposition
process of these methods. However, phase of the speech mixture is generally
used in reconstructing the target speech signal. This results in undesired
traces of interfering sources in the target signal. In this paper the spectral
phase is incorporated in the decomposition process itself. Additionally, the
complex matrix factorization problem is reduced to an NMF problem using simple
transformations. This results in effective separation of speech mixtures since
both magnitude and phase are utilized jointly in the separation process.
Improvement in source separation results are demonstrated using objective
quality evaluations on the GRID corpus.
