Paper Infomation
A Review of Audio Gene Recognition Copyright Protecting Technology
Full Text(PDF, 158KB)
Author: Xinjie Tan, jizhe cui
Abstract: The copyright stands the core competence of the cultural industry. The cultural influence depends on the standard copyright management system and supporting information processing technology in the future. This paper set the audio content copyright protection technology as starting point, and introduced the audio gene technology and research background based on characteristics. What’s more, an audio gene technology evaluation agency named MIREX established to protect copyright was introduced, which resumed audio emotion clarify standard and related technology. This paper aims to introduce audio content management system based on protect copyright technology and to provide feasible copyright thought for the musicians and enterprises, according to introduce technology research method of audio technology field based on emotion analysis and content analysis.
Keywords: Audio Genetic, Copyright Protection, Technology Research
References:
[1] Sun Jian. Study on Real-time Rhythmic Information Retrieval of Musical Audio Signal and the System Implementation [D]. : Dalian University of Technology, 2011.
[2] Wang Huimin. Music Emotion Classification Based On Regression [D]. :Nanjing University of Posts and Telecommunications, 2015.
[3] Shao Xi，Wang Hui － min. Music Emotion Classification Based on k － plane Piecewise Ｒegression [J]. Computer Technology and Development, 2015, (6): 166-170.
[4] Ji Xi Cheng. A Study on Automatic Generation of Family Music Album Based on Emotion [D]. : Nanjing University of Posts and Telecommunications, 2016.
[5] Song Liming ,LI Ming,Yan Yonghong. Pitch estimation based on harmonic salience [J]. Acta Acuatica, 2015, (2): 294-299.
[6] Xu Jie-ping，YIN Hong-yu，FAN Zi-wen. Study on cover songs identification based on phrase content [J]. Journal of Shandong University( Natural Science, 2013, (7): 68-71, 78.
[7] Gui Wen-ming, LIU Rui-fan, SHAO Xi, BAI Guang-yi. Note Onset Detection Based on Constant Q Transform [J]. Computer Engineering, 2013, (10): 283-286.
[8] Zhang Wei-wei，CHEN Zhe，YIN Fu-liang，ZHANG Jun-xing.Ｒeview on Melody Extraction from Polyphonic Music [J]. Actaelect Ronica Sinica, 2017, (4): 1000-1011.
[9] Wang Yue,Xie Lei,Yang Yulian. Adaptive whitening for real-time music beat tracking [J]. Application Research of Computers, 2009, (5): 1676-1678, 1684.
[10] Wang Tianjiang ,Chen Gang. A new method of Beat Tracking Based on CQT Features [C]//（HHME2007.）
[11] Li Na. Research and Application of Real-Time Music Beat Tracking System [D]. : Shandong University, 2011.
[12] Actaelect Ronica Sinica, 2013, (6): 1225-1230.
[13] He Ning. Beat Tracking Based on Max-Min Distance Means [D]. :Tianjin University, 2014.
[14] Wang Tianjiang ,Chen Gang. A new method of Beat Tracking Based on CQT Features [C]//（HHME2007.）: 107-113.
[15] Guo Min, Zhang Weiqiang, LIU Jia. A frame-to-note algorithm for queryby humming [J]. J Tsinghua Univ(Sci& Tech),, 2011, (4): 561-565.
[16] Li Cong. Query By Singing and Humming system [D]. :Tsinghua Univ, 2009.
[17] A J Ghias,Logan D Chamberlain.Qurey by humming musicalinformation retrieval in an audio database..SanFrancisco.
[18] He Ning. Beat Tracking Based on Max-Min Distance Means [D]. : Tianjin University, 2014.