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This paper describes an acoustic scene classification method which achievedthe 4th ranking result in the IEEE AASP challenge of Detection andClassification of Acoustic Scenes and Events 2016. In order to accomplish theensuing task, several methods are explored in three aspects: featureextraction, feature transformation, and score fusion for final decision. In thepart of feature extraction, several features are investigated for effectiveacoustic scene classification. For resolving the issue that the same sound canbe heard in different places, a feature transformation is applied for betterseparation for classification. From these, several systems based on differentfeature sets are devised for classification. The final result is determined byfusing the individual systems. The method is demonstrated and validated by theexperiment conducted using the Challenge database.

Analysis Acoustic Features for Acoustic Scene Classification and Score fusion of multi-classification systems applied to DCASE 2016 challenge