  This paper addresses the problem of under-determinded speech source
separation from multichannel microphone singals, i.e. the convolutive mixtures
of multiple sources. The time-domain signals are first transformed to the
short-time Fourier transform (STFT) domain. To represent the room filters in
the STFT domain, instead of the widely-used narrowband assumption, we propose
to use a more accurate model, i.e. the convolutive transfer function (CTF). At
each frequency band, the CTF coefficients of the mixing filters and the STFT
coefficients of the sources are jointly estimated by maximizing the likelihood
of the microphone signals, which is resolved by an Expectation-Maximization
(EM) algorithm. Experiments show that the proposed method provides very
satisfactory performance under highly reverberant environments.
