A signal subspace dimension estimator based on F-norm with application to subspace-based multi-channel speech enhancement

Although the Signal Subspace Approach(SSA)has been studied extensively for speech enhancement,no good solution has been found to identify signal subspace dimension.In this paper we present a novel signal subspace dimension estimator based on F-norm,with which subspace-based multi-channel speech enhancement is robust to adverse acoustic environments such as room reverberation and low input SNR.The results of experiments show the presented method leads to more noise reduction and less speech distortion comparing with traditional methods.