請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/54331完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 李琳山 | |
| dc.contributor.author | Yuan-Ming Liou | en |
| dc.contributor.author | 劉元銘 | zh_TW |
| dc.date.accessioned | 2021-06-16T02:50:54Z | - |
| dc.date.available | 2016-07-20 | |
| dc.date.copyright | 2015-07-20 | |
| dc.date.issued | 2015 | |
| dc.date.submitted | 2015-07-14 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/54331 | - |
| dc.description.abstract | 本論文探討在使用者加入稀疏語音標註之條件下，如何進行有效的個人相片語意檢索(semantic retrieval of personal photos)。由於近年來數位相機及智慧型手機十分普及，使用者通常會迅速累積大量的個人相片，隨之而來的一個重要問題便是如何在數量龐大的個人相片資料庫中快速瀏覽與搜尋。一般使用者都喜歡直接用語意式查詢指令(semantic query) 來找相片，例如「母親節聚餐」。但以前的個人相片檢索多半是以內容為基礎的影像檢索(content-based image retrieval, CBIR)，倚賴影像低階描述特徵且必須以一張相片作為查詢指令(query)，並不適用於使用高階語意概念(high level smenatic concepts) 的影像檢索；而以語意為基礎的影像檢索則非常倚賴影像相關的標籤(tags) 或標註(annotations)，但使用者不太可能把所有的相片都加上標註，且使用語音標註的方式又比使用鍵盤輸入的文字標註來的更為方便，所以本論文把主題設定在使用者輸入稀疏語音標註之條件下的個人相片語意檢索，亦即有少數相片上有語音標註。實現的方法主要是利用主題模型(topic model) 整合語音和影像特徵，並使用隨機漫步模型進行重新排序(re-ranking)，最後再提出使用分佈式詞會表示法(distributed word representation) 來舒緩語音特徵稀疏的問題。
首先，由於語音標註可能在任何地方被錄製，可能是非常自發性的 (spontaneous) 說話方式，所以導致辨識率低下，所以利用詞圖進行抽取字詞頻率頻率期望值(expected term frequency) 當作是語音特徵，但只有少數的相片有語音標註，所以我們必需對每張相片抽取局部(local) 與全域(global) 的影像特徵，來補充語音特徵所遺漏的資訊。而本論文利用主題模型來整合語音和影像特徵，並以此模型訓練出來的「潛藏主題」建構檢索模型。 此外，我們發現主題模型的檢索效能還有很多進步空間，所以把從主題模型檢索出的首次檢索結果(first-pass retrieval results) ，基於字詞頻率期望值、局部與全域的影像特徵計算相片之間的相似度，再套用隨機漫步模型(random walk) 演算法，讓相似度越高的相片獲得越相近的相關分數(relevance score) ，進而達成重新排序的效果，並使其檢索效能獲得相當大的進步。 此外，我們發現由於語音特徵非常稀疏，導致在訓練主題模型時就特別仰賴影像特徵，但其實語音特徵才是最主要提供使用者個人化與語意資訊的來源，所以進一步使用近年在尋找語意(semantic) 和句法(syntactic) 相關詞的任務中有良好表現的分佈式詞彙表示法，基於字詞頻率期望值與整體影像語意概念，以類似自動增加標註的方法找出相關詞並加入語音特徵中，讓原本稀疏的語音特徵不再稀疏，進而讓主題模型在訓練時考慮更多個人化與語意相關的資訊，並且也讓隨機漫步模型重新排序的效能也更好。 | zh_TW |
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| dc.description.tableofcontents | 誌謝. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i
中文摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii 一、導論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 研究動機. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 相關前人研究. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 本論文研究貢獻. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.4 章節安排. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 二、背景知識. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1 語音辨識. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.1 前端處理. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.2 統計式語音辨識. . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.1.3 聲學模型. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.4 語言模型. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.1.5 搜尋演算法與詞圖. . . . . . . . . . . . . . . . . . . . . . . . 11 2.2 檢索系統簡介. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2.1 語音文件檢索. . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2.2 以內容為基礎的影像檢索. . . . . . . . . . . . . . . . . . . . 13 2.3 主題模型. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.3.1 機率式潛藏語意分析. . . . . . . . . . . . . . . . . . . . . . . 14 2.3.2 非負矩陣分解. . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.4 圖論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.4.1 隨機漫步(Random Walk) . . . . . . . . . . . . . . . . . . . . . 20 2.5 詞彙表示法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.5.1 傳統的詞彙表示法. . . . . . . . . . . . . . . . . . . . . . . . 21 2.5.2 分佈式詞彙表示法. . . . . . . . . . . . . . . . . . . . . . . . 22 三、以主題模型整合語音和影像特徵實現個人相片語意檢索系統. . . . . . . 25 3.1 簡介. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.2 系統架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 3.3 影像特徵抽取. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.3.1 視覺詞作為局部影像特徵. . . . . . . . . . . . . . . . . . . . 28 3.3.2 整體影像語意概念作為全域影像特徵. . . . . . . . . . . . . . 31 3.4 語音特徵抽取. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.5 建立相片文件. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.6 利用主題模型建構檢索模型. . . . . . . . . . . . . . . . . . . . . . . 35 3.6.1 機率式潛藏語意分析檢索模型. . . . . . . . . . . . . . . . . . 35 3.6.2 非負矩陣分解檢索模型. . . . . . . . . . . . . . . . . . . . . . 36 3.7 實驗基礎設置. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.7.1 個人相片資料庫. . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.7.2 個人相片語音標註收集過程. . . . . . . . . . . . . . . . . . . 38 3.7.3 語音辨識結果. . . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.7.4 實驗配置. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.7.5 評估方式. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 3.8 實驗結果與分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 3.9 本章總結. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 四、利用隨機漫步模型增強個人相片語意檢索系統. . . . . . . . . . . . . . . 43 4.1 簡介. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.2 系統架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.3 隨機漫步模型. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.3.1 裁剪. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.3.2 單層隨機漫步模型. . . . . . . . . . . . . . . . . . . . . . . . 46 4.3.3 雙層隨機漫步模型. . . . . . . . . . . . . . . . . . . . . . . . 47 4.4 基本實驗配置. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 4.5 實驗結果與討論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.5.1 整體實驗結果. . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.5.2 探討內插參數 與裁剪方法. . . . . . . . . . . . . . . . . . . 53 4.6 本章總結. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 五、使用分佈式詞彙表示法加強稀疏語音標注之個人相片語意檢索系統. . . 57 5.1 簡介. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5.2 系統架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 5.3 使用分佈式詞彙表示法模型. . . . . . . . . . . . . . . . . . . . . . . 58 5.3.1 遞迴式類神經網路語言模型. . . . . . . . . . . . . . . . . . . 60 5.3.2 連續詞袋模型. . . . . . . . . . . . . . . . . . . . . . . . . . . 64 5.3.3 跳躍文法模型. . . . . . . . . . . . . . . . . . . . . . . . . . . 66 5.4 從詞彙表示法模型找出相關詞加入相片文件. . . . . . . . . . . . . . 67 5.5 基本實驗配置. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 5.6 實驗結果與分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 5.6.1 使用分佈式詞彙表示法模型. . . . . . . . . . . . . . . . . . . 70 5.6.2 再使用隨機漫步模型之結果. . . . . . . . . . . . . . . . . . . 73 5.7 本章總結. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 六、結論與展望. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 6.1 結論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 6.2 未來研究方向. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 6.2.1 語音辨識系統的改進. . . . . . . . . . . . . . . . . . . . . . . 79 6.2.2 影像特徵上的改進. . . . . . . . . . . . . . . . . . . . . . . . 80 6.2.3 整合語音和影像特徵模型的改進. . . . . . . . . . . . . . . . 80 6.2.4 自動標註之研究. . . . . . . . . . . . . . . . . . . . . . . . . . 80 參考文獻. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 | |
| dc.language.iso | zh-TW | |
| dc.subject | 個人相片 | zh_TW |
| dc.subject | 個人相片 | zh_TW |
| dc.subject | 隨機漫步 | zh_TW |
| dc.subject | 詞彙表示法 | zh_TW |
| dc.subject | 檢索 | zh_TW |
| dc.subject | 檢索 | zh_TW |
| dc.subject | 隨機漫步 | zh_TW |
| dc.subject | 詞彙表示法 | zh_TW |
| dc.subject | random walk | en |
| dc.subject | retrieval | en |
| dc.subject | random walk | en |
| dc.subject | word representation | en |
| dc.subject | personal photos | en |
| dc.subject | retrieval | en |
| dc.subject | word representation | en |
| dc.subject | personal photos | en |
| dc.title | 使用隨機漫步及分佈式詞彙表示法增強個人相片之語意檢索 | zh_TW |
| dc.title | Enhanced Semantic Retrieval of Personal Photos Using Random Walk and Distributed Word Representations | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 103-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 李宏毅,鄭秋豫,王小川,陳信宏,簡仁宗 | |
| dc.subject.keyword | 檢索,隨機漫步,詞彙表示法,個人相片, | zh_TW |
| dc.subject.keyword | retrieval,random walk,word representation,personal photos, | en |
| dc.relation.page | 89 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2015-07-14 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
| 顯示於系所單位： | 電信工程學研究所 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-104-1.pdf 未授權公開取用 | 4.9 MB | Adobe PDF |
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