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Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/19860
標題: 利用關聯式規則解決台語文轉音系統中一詞多音之歧異
Applying Association Rules in Solving the Polysemy Problem in a Chinese to Taiwanese TTS System
作者: 李尉綸
Li, Wei-Lun
關鍵字: 關聯式規則;Association Rules;關聯式分類;一詞多音;台語文轉音系統;監督式學習;Associative Classification;polysemy;Chinese to Taiwanese TTS system;supervised learning
出版社: 資訊網路多媒體研究所
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摘要: 
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。

In 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.
URI: http://hdl.handle.net/11455/19860
其他識別: U0005-1508201220493100
Appears in Collections:資訊網路與多媒體研究所

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