STUDY ON THE RECOGNITION OF OBJECTIONABLE AUDIO

Author:

SHI ZIQIANG1,GAO BOYANG1,ZHENG TIERAN1,HAN JIQING1

Affiliation:

1. School of Computer Science and Technology, Harbin Institute of Technology, P. O. Box 321, Harbin, Heilongjiang 150001, P. R. China

Abstract

In this paper, a novel method from the feature — porno-sounds recognition — point of view is proposed to detect adult video sequences automatically which may serve as a verification step, a supplementary method or an independent detector. To the specificity of erotic sound, its feature analysis is given. Based on the popular features, histograms and contours are introduced as new sets of features. At the same time due to the complexity of outside data, a general framework called in-class clustering is proposed which selects the most representative subclass for training and classification. All these efforts increase the recall rate and decrease the false positive rate. Experiments on real data from the Internet indicate that the proposed method yields superior performance with 89.17% recall rate and 10.78% false positive rate being achieved.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Identification of Objectionable Audio Segments Based on Pseudo and Heterogeneous Mixture Models;IEEE Transactions on Audio, Speech, and Language Processing;2013-03

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