The Subspace Approach as a First Stage in Speech Enhancement
To increase the performance of the communication systems and other applications related to speech or speaker recognition, it is usual to incorporate a preprocessing stage for speech enhancement before it enters a specific system. Although the signal subspace approach is very useful, it becomes less effective when the signal to noise ratio (SNR) is lower than 10 dB due to possible inaccuracies in estimating the noise, whose action over the different phonemes and frequency bands is far from uniform, even considering white noise. The noisy signal projection over the signal subspace can be view as a first stage in the speech enhancement process that will be complement with additional techniques. A critical point is estimating the signal subspace dimension. It depends of the noise variance but on SNR too, which varies on the different temporal segments of speech and the frequency band. Then it is proposed to work over frames in each critical band using as threshold noise variance affected by a factor depending of the particular segment SNR.
signal subspace dimension singular value descomposition auditory system signal distortion