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An energy-constrained signal subspace ECSS method is proposed for speech enhancement and recognition under an additive colored noise condition. The key idea is to match the short-time energy of the enhanced speech signal to the unbiased estimate of the short-time energy of the clean speech, which is proven very e ective for improving the estimation of the noise-like, low-energy segments in speech signal. The colored noise is modelled by an autoregressive AR process. A modi ed covariance methoddoi:10.1109/icassp.1998.674446 dblp:conf/icassp/HuangZ98 fatcat:ojj5l656cnhoraalcpk6vx3eka