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Description
A noise estimation algorithm is proposed for single channel
speech enhancement. By comparing the noise estimate
with the short term noise and speech at every time frame, the
noise estimate is efficiently updated by using a fixed stepsize.
The step size is optimized based on the speech quality
performance and the noise tracking capability. The proposed
technique is capable of tracking noise spectrum variations,
while remaining robust to the speech onsets. In addition,
the noise estimator requires low computational complexity,
which makes it effective for real time implementation in battery
operated equipment. Simulation results show that the
proposed method can achieve good speech quality and efficient
noise tracking performance when compared to existing
methods.