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Acoustic scene classification using recurrence quantification analysis

재발량 분석을 이용한 음향 상황 인지

Park, Sangwook;Choi, Woohyun;Ko, Hanseok
박상욱;최우현;고한석

  • Received : 2015.10.08
  • Accepted : 2015.11.05
  • Published : 2016.01.31

Abstract

Since a variety of sound occur in same place and similar sound occurs in other places, the performance of acoustic scene classification is not guaranteed in case of insufficient training data. A Bag of Words (BOW) based histogram feature is foreseen as a method to overcome the problem. However, since the histogram features is made by using a feature distribution, the ordering of sequence of features is ignored. A temporal information such as periodicity and stationarity are also important for acoustic scene classification. In this paper, temporal features about a periodicity and a stationarity are extracted by using a recurrent quantification analysis. In the experiment, performance of the proposed method is shown better than other baseline methods.

Keywords

Acoustic scene classification;Bag of Words (BOW);Recurrence quantification analysis;Support vector machine

References

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Acknowledgement

Grant : BK21플러스

Supported by : 고려대학교