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Acoustic soundscapes can be made up of background sound events and foreground sound events. Many times, either the background (or the foreground) may provide useful cues in discriminating one soundscape from another. A part of the background or a part of the foreground can be suppressed by using subspace projections. These projections can be learnt by utilising the framework of robust principal component analysis. In this work, audio signals are represented as embeddings from a convolutionaldoi:10.21437/interspeech.2020-2476 dblp:conf/interspeech/DevalrajuMRD20 fatcat:2nuzfu6ezvf73gnjx4hsfbpxam