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A dictionary learning based audio source classification algorithm is proposedto classify a sample audio signal as one amongst a finite set of differentaudio sources. Cosine similarity measure is used to select the atoms duringdictionary learning. Based on three objective measures proposed, namely, signalto distortion ratio (SDR), the number of non-zero weights and the sum ofweights, a frame-wise source classification accuracy of 98.2% is obtained fortwelve different sources. Cent percent accuracy has been obtained using movingSDR accumulated over six successive frames for ten of the audio sources tested,while the two other sources require accumulation of 10 and 14 frames.

A dictionary learning and source recovery based approach to classify diverse audio sources