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政大機構典藏 > 資訊學院 > 資訊科學系 > 學位論文 > Item 140.119/32652

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/32652

Title:	個人化情緒／情境音樂檢索系統 Personalized Music Retrieval Based on Emotions / Situations
Authors:	李侃儒 Li, Kan-Ru
Contributors:	陳良弼 Chen, Arbee 李侃儒 Li, Kan-Ru
Keywords:	音樂檢索情緒情境個人化音樂表示法音樂特徵自動調整重要性 music retrieval emotion situation personalization music representation features re-weighting
Date:	2005
Issue Date:	2009-09-17 13:56:51 (UTC+8)
Abstract:	在本論文中我們提出了一種個人化情緒／情境音樂檢索方法。主要的概念為根據使用者的feedback來找出符合該使用者情緒／情境的音樂在features上所具備的特性，藉此達到個人化的效果。為了更明確表示出音樂的特性，我們利用統計features分布情況的方式來做為音樂的表示法。同時，定義了兩層features自動weighting的方法來決定每個feature在不同情緒／情境下的鑑別度。最後，我們將探討音樂特性與音色對不同的情緒／情境會造成什麼樣的影響，並試著分析音樂與情緒／情境間的關係。 In this paper, an approach for personalized music retrieval based on emotions / situations is proposed. The main concept is to find out the properties of music that caused the user have emotions / situations responses via the user feedback. And using the user feedback will help us to establish a personalized music retrieval system based on emotions / situations. To represent the music properties clearly, we proposed a new method of music representation based on statistics. And we defined a two-phase features re-weighting method to find out the importance of features in different emotions / situations. At last, we will discuss the influence of music properties and timbre on different emotions / situations, and try to analyze the relationship between the emotions / situations.
Reference:	[1] 孟憲福主譯, 殷于涵審校(2004), S. Sadie and A. Latham原著, 劍橋音樂入門（The Cambridge Illustrated Guide of Music）, 台北市：果實出版, 城邦文化發行. [2] D. Liu, L. Lu, and H.J. Zhang, 2003. “Automatic Mood Detection from Acoustic Music Data.” International Symposium on Music Information Retrieval. [3] Y. Feng, Y. Zhuang, and Y. Pan, 2003. “Music Information Retrieval by Detecting Mood via Computational Media Aesthetics,” IEEE/WIC International Conference on Web Intelligence, 235-241. [4] D. Yang and W.S. Lee, 2004. “Disambiguating Music Emotion Using Software Agents.” International Symposium on Music Information Retrieval, 218-223. [5] T. Li and M. Ogihara, 2003. “Detecting emotion in music,” International Symposium on Music Information Retrieval, 239-240. [6] 游恆山編譯(1990), Philip G. Zimbardo原著, 心理學, 台北市：五南圖書公司. [7] 王毓雅, 如何進行幼兒音樂教學～由幼兒音樂概念發展觀之, 國教新知第47卷第3期. [8] S. Khalfa, I. Peretz, B. Jean-Pierre, and R. Manon , 2002. “Event-related skin conductance responses to musical emotions in humans. ” Neuroscience Letters, 328, 145-149. [9] N. Gosselin, I. Peretz, M. Noulhiane, D. Hasboun, C. Beckett, M. Baulac, and S. Samson, 2005. “Impaired recognition of scary music following unilateral temporal lobe excision. ” Brain, 128, 628-640. [10] A. Chen, M. Chang, J. Chen, J. L. Hsu, C. H. Hsu, and Spot Y. S. Hua, 2000. “Query by Music Segments: An Efficient Approach for Song Retrieval.” Proceedings of the IEEE International Conference on Multimedia and Expro, 873-876. [11] C. C. Liu, J. L. Hsu, and A. Chen, 1999. “An Approximate String Matching Algorithm for Content-Based Music Data Retrieval,” Proceedings of the IEEE International Conference on Multimedia Computing and Systems, 451-456. [12] J. Russell.“A circumplex model of affect, ” Journal of Personality and Social Psychology, 39, 1161-1178, 1980 [13] 陳美如主譯, 洪小萍、石曉蓉編輯, 篠田知璋、加藤美知子主編, 日野原重明審訂, 標準音樂治療入門, 台北市：五南圖書公司. [14] 謝俊逢, 音樂療法-理論與方法, 台北市：大陸書局
Description:	碩士國立政治大學資訊科學學系 93753012 94
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0093753012
Data Type:	thesis
Appears in Collections:	[資訊科學系] 學位論文

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