An Efficient Pre-Processing Scheme to Improve the Sound Source Localization System in Noisy Environment

In this study, we introduce an efficient pre-processing scheme for direction of arrival (DOA) estimation, which is capable of reducing the noise and reverberation effects in speech sound source localization. Furthermore, this presented system is also suitable for far-field speech localization. The adopted method of this proposed system can be simply subdivided into three stages: Linear phase-difference approximation, covariance matrix reconstruction, and frequency bin selection. The first two stages can initially decrease the influences of noise and reverberation; the last stage is used to filter the noise frequency bands according to the eigenvalue decomposition (EVD) of the covariance matrix. The experimental results show that our proposed system has effective performance of detecting different directions of speeches. For different signalto-noise ratios (SNRs) speech signals, the average estimation errors can be decreased by about 5 to 7.5 degrees.