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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