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| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 李琳山(Lin-shan Lee) | |
| dc.contributor.author | Chien-yu Huang | en |
| dc.contributor.author | 黃健祐 | zh_TW |
| dc.date.accessioned | 2022-11-23T09:20:57Z | - |
| dc.date.available | 2021-08-06 | |
| dc.date.available | 2022-11-23T09:20:57Z | - |
| dc.date.copyright | 2021-08-06 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-07-27 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80011 | - |
| dc.description.abstract | 語音轉換（Voice Conversion）是不改變語句中的語言內容（Linguistic Content）或音素結構（Phoneme Structure），而去修改語音訊號中某些其他特定資訊的技術，其中以變換語者音色（Vocal Timbre）的語者轉換最為常見。近年來，隨著機器學習等相關技術的發展，我們已能夠達成任意對任意（Any-to-any）的語者轉換，亦即可將任意語句中的語者音色修改為任意一位其他語者的。然而，以現有技術而言，成功的語音轉換必須以乾淨而無雜訊的語音訊號作為輸入。另一方面，隨著技術不斷進步，語音轉換極有可能被用來偽造他人的聲音。因此，如何強化語音轉換技術在雜訊環境的表現，以及如何保護我們的語者音色不被「竊取」，便成為了相當重要的研究方向。 本論文首先分析現有語音轉換模型在雜訊環境下的強健性（Robustness），在輸入訊號中加入雜訊，並衡量轉換結果的失真程度。為了提升模型的表現，本論文使用語音增強（Speech Enhancement）模型進行預處理，將訊號中的雜訊去除後，再輸入至語音轉換模型。同時，本論文也提出以去雜訊損失作為語音轉換模型的訓練目標，使其能夠在不利用上述預處理的情況下，依然能夠減少轉換的失真。實驗結果顯示，兩種方法皆能有效提升語音轉換模型在雜訊環境下的表現，並且端對端的去雜訊比表徵層級上的處理更能夠提升轉換結果的品質。 接著，本論文提出三種針對語音轉換模型的對抗式攻擊（Adversarial Attack），透過在輸入訊號中加入人類無法感知的特殊雜訊，使得語音轉換模型無法成功，並以此作為保護個人語音不受濫用的手段。此外，本論文也使用語音增強以「抵禦」提出之攻擊方法。實驗結果顯示，即便是在模型參數未知的情況下，本論文所提出之攻擊方法仍然能夠大幅改變模型的轉換結果，使其語者音色與所期望者大相逕庭；另一方面，語音增強模型不僅能作用於人類感知中的一般雜訊，亦可在一定程度上抹除極微小的對抗式雜訊，並提升語音轉換模型在攻擊下的轉換效果。 | zh_TW |
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| dc.description.tableofcontents | 目錄 誌謝 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i 中文摘要 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii 英文摘要 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv 一、導論 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 研究動機 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 研究方向及貢獻 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 章節安排 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 二、背景知識 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1 深層類神經網路 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.1 簡介 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.2 卷積式類神經網路 . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.3 遞迴式類神經網路 . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2 對抗式攻擊 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2.1 簡介 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2.2 特定目標與非特定目標攻擊 . . . . . . . . . . . . . . . . . . . 11 2.2.3 黑箱與白箱攻擊 . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.3 語音轉換 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.3.1 簡介 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.3.2 任意對任意語音轉換 . . . . . . . . . . . . . . . . . . . . . . . 15 2.4 語音增強 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.5 本章總結 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 三、語音轉換於一般雜訊環境下之表現 . . . . . . . . . . . . . . . . . . . . . . 20 3.1 簡介 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.2 基於語音增強之語音轉換 . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.3 以去雜訊損失訓練之語音轉換 . . . . . . . . . . . . . . . . . . . . . . 22 3.3.1 端對端去雜訊 . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.3.2 表徵層級去雜訊 . . . . . . . . . . . . . . . . . . . . . . . . . . 23 3.4 實驗設定 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.4.1 資料集 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.4.2 與語音增強模型串聯之實驗 . . . . . . . . . . . . . . . . . . . 27 3.4.3 實作細節 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.5 實驗結果與分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.5.1 評估方法 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.5.2 實驗結果 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.6 本章總結 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 四、語音轉換之對抗式攻擊與隱私保護 . . . . . . . . . . . . . . . . . . . . . . 45 4.1 簡介 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.2 端對端對抗式攻擊 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 4.3 基於語者表徵之對抗式攻擊 . . . . . . . . . . . . . . . . . . . . . . . 48 4.4 基於轉換結果之語者表徵之對抗式攻擊 . . . . . . . . . . . . . . . . . 49 4.5 基於語音增強之防禦 . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 4.6 以對抗式攻擊保護個人語音 . . . . . . . . . . . . . . . . . . . . . . . 51 4.7 實驗設定 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 4.7.1 模型與資料集 . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 4.7.2 實作細節 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 4.8 實驗結果與分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 4.8.1 評估方法 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 4.8.2 實驗結果 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 4.9 本章總結 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 五、結論與展望 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 5.1 研究貢獻與討論 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 5.2 未來展望 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 參考文獻 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 | |
| dc.language.iso | zh-TW | |
| dc.subject | 雜訊強健性 | zh_TW |
| dc.subject | 對抗式攻擊 | zh_TW |
| dc.subject | 語音轉換 | zh_TW |
| dc.subject | Noise Robustness | en |
| dc.subject | Voice Conversion | en |
| dc.subject | Adversarial Attack | en |
| dc.title | 語音轉換之雜訊強健性及隱私保護 | zh_TW |
| dc.title | Noise Robustness and Privacy Protection in Voice Conversion | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.author-orcid | 0000-0003-4927-1293 | |
| dc.contributor.oralexamcommittee | 鄭秋豫(Hsin-Tsai Liu),王小川(Chih-Yang Tseng),陳信宏,簡仁宗,李宏毅 | |
| dc.subject.keyword | 語音轉換,雜訊強健性,對抗式攻擊, | zh_TW |
| dc.subject.keyword | Voice Conversion,Noise Robustness,Adversarial Attack, | en |
| dc.relation.page | 99 | |
| dc.identifier.doi | 10.6342/NTU202101515 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2021-07-27 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| Appears in Collections: | 電機工程學系 | |
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| File | Size | Format | |
|---|---|---|---|
| U0001-1607202115262400.pdf | 3.34 MB | Adobe PDF | View/Open |
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