dc.contributor.advisor | 陳良弼 | zh_TW |
dc.contributor.advisor | Chen, Arbee | en_US |
dc.contributor.author (Authors) | 李侃儒 | zh_TW |
dc.contributor.author (Authors) | Li, Kan-Ru | en_US |
dc.creator (作者) | 李侃儒 | zh_TW |
dc.creator (作者) | Li, Kan-Ru | en_US |
dc.date (日期) | 2005 | en_US |
dc.date.accessioned | 17-Sep-2009 13:56:51 (UTC+8) | - |
dc.date.available | 17-Sep-2009 13:56:51 (UTC+8) | - |
dc.date.issued (上傳時間) | 17-Sep-2009 13:56:51 (UTC+8) | - |
dc.identifier (Other Identifiers) | G0093753012 | en_US |
dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/32652 | - |
dc.description (描述) | 碩士 | zh_TW |
dc.description (描述) | 國立政治大學 | zh_TW |
dc.description (描述) | 資訊科學學系 | zh_TW |
dc.description (描述) | 93753012 | zh_TW |
dc.description (描述) | 94 | zh_TW |
dc.description.abstract (摘要) | 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。 | zh_TW |
dc.description.abstract (摘要) | 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. | en_US |
dc.description.tableofcontents | 第一章 導論.................................................11.1 背景...................................................11.2 音樂檢索................................................11.2.1 Annotation-based music information retrieval.........11.2.2 Content-based music information retrieval............21.2.2.1 Query by Music Segments: An Efficient Approach for Song Retrieval [10]........................................21.2.2.2 An Approximate String Matching Algorithm for Content-Based Music Data Retrieval [11]....................61.2.3 Emotion/Situation-based music information retrieval.................................................131.2.3.1 利用音樂與心理方面所建立的模型進行音樂的分類 [2][3]....141.2.3.1.1 Automatic Mood Detection from Acoustic Music Data [2].......................................................141.2.3.1.2 Music Information Retrieval by Detecting Mood via Computational Media Aesthetics [3]........................161.2.3.2 根據預先分類好的歌詞資料利用decision tree等方式建立歌詞分類法則[4] ................................................231.2.3.2.1 Disambiguating Music Emotion Using Software Agents [4]...............................................231.2.3.3 根據預先分類好的音樂資料利用SVM等方式建立音樂分類法則 [5]......................................................241.2.3.3.1 Detecting emotion in music [5] ................241.4 個人化音樂情緒的重要性..................................251.5 系統架構..............................................271.6 論文結構..............................................28第二章 音樂檢索與相似度計算..................................29第三章 即時個人化..........................................34第四章 實驗結果............................................364.1 情緒與情境的定義.......................................364.2 系統實作與介紹.........................................374.3 實驗結果及數據.........................................41第五章 結論...............................................51參考資料..................................................52 | zh_TW |
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dc.format.mimetype | application/pdf | - |
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dc.format.mimetype | application/pdf | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en_US | - |
dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0093753012 | en_US |
dc.subject (關鍵詞) | 音樂檢索 | zh_TW |
dc.subject (關鍵詞) | 情緒 | zh_TW |
dc.subject (關鍵詞) | 情境 | zh_TW |
dc.subject (關鍵詞) | 個人化 | zh_TW |
dc.subject (關鍵詞) | 音樂表示法 | zh_TW |
dc.subject (關鍵詞) | 音樂特徵自動調整重要性 | zh_TW |
dc.subject (關鍵詞) | music retrieval | en_US |
dc.subject (關鍵詞) | emotion | en_US |
dc.subject (關鍵詞) | situation | en_US |
dc.subject (關鍵詞) | personalization | en_US |
dc.subject (關鍵詞) | music representation | en_US |
dc.subject (關鍵詞) | features re-weighting | en_US |
dc.title (題名) | 個人化情緒/情境音樂檢索系統 | zh_TW |
dc.title (題名) | Personalized Music Retrieval Based on Emotions / Situations | en_US |
dc.type (資料類型) | thesis | en |
dc.relation.reference (參考文獻) | [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. | zh_TW |
dc.relation.reference (參考文獻) | [2] D. Liu, L. Lu, and H.J. Zhang, 2003. “Automatic Mood Detection from Acoustic Music Data.” International Symposium on Music Information Retrieval. | zh_TW |
dc.relation.reference (參考文獻) | [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. | zh_TW |
dc.relation.reference (參考文獻) | [4] D. Yang and W.S. Lee, 2004. “Disambiguating Music Emotion Using Software Agents.” International Symposium on Music Information Retrieval, 218-223. | zh_TW |
dc.relation.reference (參考文獻) | [5] T. Li and M. Ogihara, 2003. “Detecting emotion in music,” International Symposium on Music Information Retrieval, 239-240. | zh_TW |
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dc.relation.reference (參考文獻) | [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. | zh_TW |
dc.relation.reference (參考文獻) | [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. | zh_TW |
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