An energy-constrained signal subspace method for speech enhancement and recognition in colored noise

J. Huang, Y. Zhao
Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181)  
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 method
more » ... covariance method is used to estimate the AR parameters of the colored noise and a prewhitening lter is constructed based on the estimated parameters. The performance of the proposed algorithm was evaluated using the TI46 digit database and the TIMIT continuous speech database. It was found that the ECSS method can signi cantly improve the signal-to-noise ratio SNR and word recognition accuracy WRA for isolated digits and continuous speech under various SNR conditions.
doi:10.1109/icassp.1998.674446 dblp:conf/icassp/HuangZ98 fatcat:ojj5l656cnhoraalcpk6vx3eka