A robust sound event recognition framework under TV playing conditions

In this paper, we address the problem of performing sound event recognition tasks in the presence of television playing in a home environment. Our proposed framework consist of two modules: (1) a novel regression-based noise cancellation (RNC), a preprocessing which utilises a addition reference microphone placed near the television to reduce the noise. RNC learns an empirical mapping instead of the convention adaptive methods to achieve better noise reduction. (2) An improved subband power distribution image feature (iSPD-IF) which build on our existing classification framework by enhancing the feature extraction. A comprehensive experiment is carried out on our recorded data, which demonstrates high classification accuracy under severe television noise.