  This paper addresses the automatic classification of X-rated videos by
analyzing its obscene sounds. In this paper, obscene sounds refer to audio
signals generated from sexual moans and screams during sexual scenes. By
analyzing various sound samples, we determined the distinguishable
characteristics of obscene sounds and propose a repeated curve-like spectrum
feature that represents the characteristics of such sounds. We constructed
6,269 audio clips to evaluate the proposed feature, and separately constructed
1,200 X-rated and general videos for classification. The proposed feature has
an F1-score, precision, and recall rate of 96.6%, 98.2%, and 95.2%,
respectively, for the original dataset, and 92.6%, 97.6%, and 88.0% for a noisy
dataset of 5dB SNR. And, in classifying videos, the feature has more than a 90%
F1-score, 97% precision, and an 84% recall rate. From the measured performance,
X-rated videos can be classified with only the audio features and the repeated
curve-like spectrum feature is suitable to detect obscene sounds.
