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dc.contributorMing-Shing Yuen_US
dc.contributor.authorLi, Wei-Lunen_US
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dc.description.abstract在中文轉台語文轉音系統中,一詞多音問題一直是一個急待解決的問題。在台語中,一個詞可能擁有多種發音,如果因為一詞多音問題造成標音上的錯誤,將導致台語語音合成系統無法合成正確的語音。本論文將針對台語文轉音系統中的一詞多音問題進行探討。 為了解決這個問題,我們利用關聯式規則來預測台語多音詞的發音。本文針對六種常見的多音詞進行實驗,分別為『上』、『下』、『不』、『你』、『我』、『他』等詞。經過實驗分別得到的正確率為93.99%、94.44%、77.82%、95.11%、96.35%、95.99%。實驗結果顯示,相較於現有的實驗方法,本論文提出的方法對於上述六個多音詞皆達到更高的正確率。zh_TW
dc.description.abstractIn a Chinese to Taiwanese Text-to-Speech(TTS) system, the polysemy problem is one of the important issues. In Taiwanese, one word may have several pronunciations. A Taiwanese TTS System can''t work well if wrong pronunciation is synthesized. This research focuses on the polysemy problems in a Chinese to Taiwanese TTS system. In solving this problem, we apply association rules to predict the pronunciation for the polysemy words in Taiwanese. We focused on six commonly used words with polysemy problem in this thesis. They are 『上』(up), 『下』(down), 『不』(no) , 『你』(you), 『我』(I), and 『他』(he/she) . The accuracies of experimental results are 93.99%, 94.44%, 77.82%, 95.11%, 96.35% and 95.99%, respectively. Experiment results show that the proposed approach can achieve higher precisions in these six words than the existing methods.en_US
dc.description.tableofcontents第一章 緒 論 1 1.1研究動機及方向 1 1.2中文轉台語文轉音系統之架構 2 1.3台語文轉音系統中的文句分析模組 4 1.3論文架構 7 第二章 台語一詞多音現象與相關研究 9 2.1台語一詞多音現象 9 2.2台語一詞多音問題的相關研究 12 2.2.1語言模型和決策樹的組合式策略 12語言模型 12決策樹 13組合式策略 15 2.2.2階層式方法 16 2.2.3規則轉換學習法 20 第三章 研究方法 24 3.1關聯式規則介紹 24 3.2利用關聯式規則解決台語一詞多音問題 27 3.2.1特徵擷取 28 3.2.2生成規則 29 第四章 實驗結果 34 4.1實驗設定 34 4.1.1實驗語料 34 4.1.2訓練與測試語料分配比例 39 4.2參數設定之實驗 40 4.2.2最低出現頻率的設定實驗 41 4.2.3最低信心度設定實驗 43 4.2.4規則長度上限設定之實驗結果 45 4.3追加詞義特徵 46 4.3.1廣義知網中文詞知識庫(E-HOWNET)介紹 47 4.3.2追加詞義特徵之實驗 49 4.4外部測試與各種實驗方法比較 52 第五章 結論 54zh_TW
dc.subjectAssociation Rulesen_US
dc.subjectAssociative Classificationen_US
dc.subjectChinese to Taiwanese TTS systemen_US
dc.subjectsupervised learningen_US
dc.titleApplying Association Rules in Solving the Polysemy Problem in a Chinese to Taiwanese TTS Systemen_US
dc.typeThesis and Dissertationzh_TW
Appears in Collections:資訊網路與多媒體研究所


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