A Time–Frequency Domain Blind Source Separation Method for Underdetermined Instantaneous Mixtures

We propose a new method for underdetermined blind source separation based on the time–frequency domain. First, we extract the time–frequency points that are occupied by a single source, and then, we use clustering methods to estimate the mixture matrix A. Second, we use the parallel factor (PARAFAC), which is based on nonnegative tensor factorization, to synthesize the estimated source. Simulations using mixtures of audio and speech signals show that this approach yields good performance.