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Table 3 Different audio classes in the dataset and the number of signals in each class

From: Discriminant non-stationary signal features’ clustering using hard and fuzzy cluster labeling

Classes Dataset Average accuracy
   TF + soft labeling (%) TF + GMM (%) MFCC + GMM (%)
Human/non-human Non-human: aircraft, piano, animal, bird 96 86 79
  Human: male and female speeches    
Human/music Music: piano, flute, drum 98 68 71
  Human: male and female speeches    
Natural/artificial Natural: male, female, bird, animal, insect 91 63 62
  Artificial: helicopter, airplane, piano, flute, drum    
Human/Nature Nature: animal, insect, bird 98 83 75
  Human: male and female speeches    
Aircraft/music Music: piano, flute, drum 98 76 89
  Aircraft: helicopter, airplane