  This paper describes an acoustic scene classification method which achieved
the 4th ranking result in the IEEE AASP challenge of Detection and
Classification of Acoustic Scenes and Events 2016. In order to accomplish the
ensuing task, several methods are explored in three aspects: feature
extraction, feature transformation, and score fusion for final decision. In the
part of feature extraction, several features are investigated for effective
acoustic scene classification. For resolving the issue that the same sound can
be heard in different places, a feature transformation is applied for better
separation for classification. From these, several systems based on different
feature sets are devised for classification. The final result is determined by
fusing the individual systems. The method is demonstrated and validated by the
experiment conducted using the Challenge database.
