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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.11 No.2
- 발행연도
- 2022.4
- 수록면
- 92 - 96 (5page)
이용수
초록· 키워드
오류제보하기
In this paper, an effective system for discriminating violent scenes in movies from audio signals alone is proposed. The technology for automatic discrimination of violent scenes is one of the most crucial aspects of media filtering, protecting users from undesired media. Previous studies have conducted violent scene discrimination using a mel spectrogram and 2D convolutional neural networks (CNNs); however, the mel spectrogram cannot extract mutual information from audio, and 2D CNNs are unsuitable for audio. Therefore, these models do not yield good performance. The system proposed in this paper extracts audio features by using Wav2vec 2.0, which can extract mutual information from audio. The features of the extracted audio are inputted to a 1D CNN and long short-term memory (LSTM), which are algorithms suitable for audio, and violent scenes are discriminated through fully connected and softmax layers. To evaluate the proposed system, violent scenes are discriminated using the Violent Movie Scenes Dataset (VMD). As a result, the accuracy of the proposed system when discriminating violent scenes is 96.25%, providing better performance than in previous studies.
목차
Abstract
1. Introduction
2. Technologies of the Proposed System
3. Violent Scene Discrimination
4. Experiment
5. Conclusion
References
참고문헌 (13)
참고문헌 신청
Gentile, Douglas A., et al. “Media Violence as a Risk Factor for Children: A Longitudinal Study.” American Psychological Society 16th Annual Convention, Chicago, IL. 2004. Article (CrossRef Link)
Shafaei, M.; Samghabadi, N.S.; Kar, S.; Solorio, T. “Rating for Parents: Predicting Children Suitability Rating for Movies Based on Language of the Movies.” arXiv 2019, arXiv:1908.07819. Article (CrossRef Link)
Mu, Guankun, Haibing Cao, and Qin Jin. “Violent Scene Detection Using Convolutional Neural Networks and Deep Audio Features.” Chinese Conference on Pattern Recognition. Springer, Singapore, 2016. Article (CrossRef Link)
Sarman, Sercan, and Mustafa Sert. “Audio Based Violent Scene Classification Using Ensemble Learning.” 2018 6th International Symposium on Digital Forensic and Security (ISDFS). IEEE, 2018. Article (CrossRef Link)
Y. Potharaju, M. Kamsali, and C. R. Kesavari, “Classification of Ontological Violence Content Detection through Audio Features and Supervised Learning,” International Journal of Intelligent Engineering and Systems, Vol. 12, No. 3, pp. 20–230, 2019. Article (CrossRef Link)
Shafaei, M.; Samghabadi, N.S.; Kar, S.; Solorio, T. “Rating for Parents: Predicting Children Suitability Rating for Movies Based on Language of the Movies.” arXiv 2019, arXiv:1908.07819. Article (CrossRef Link)
Mu, Guankun, Haibing Cao, and Qin Jin. “Violent Scene Detection Using Convolutional Neural Networks and Deep Audio Features.” Chinese Conference on Pattern Recognition. Springer, Singapore, 2016. Article (CrossRef Link)
Sarman, Sercan, and Mustafa Sert. “Audio Based Violent Scene Classification Using Ensemble Learning.” 2018 6th International Symposium on Digital Forensic and Security (ISDFS). IEEE, 2018. Article (CrossRef Link)
Y. Potharaju, M. Kamsali, and C. R. Kesavari, “Classification of Ontological Violence Content Detection through Audio Features and Supervised Learning,” International Journal of Intelligent Engineering and Systems, Vol. 12, No. 3, pp. 20–230, 2019. Article (CrossRef Link)
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