%0 Journal Article
%T English accent assignment based on morphological rules and machine learning<br>英文文语转换系统中基于形态规则和机器学习的重音标注算法
%A WANG Yong-sheng
%A LI Mei
%A <br>王永生
%A 李梅
%J 计算机应用
%D 2008
%I 
%X Accent assignment of out-of-vocabulary is a very important component besides letter-to-phoneme Conversion in English Text-To-Speech (TTS). Considering that primary accent is much more important and simpler than secondary accent, their assignment was conducted separately. A hybrid algorithm of morphological rules and machine learning was presented to tackle the assignment of primary accent. And a machine learning algorithm was proposed to handle the assignment of secondary accent. After 10-fold cross validation, the average accuracy of primary and secondary accent assignment reached 94.4% and 86.9% respectively, and the total accuracy was 83.6%.
%K Accent Assignment
%K Text-to-Speech
%K Out-of-vocabulary
%K Machine Learning<br>文语转换
%K 未登录词
%K 重音标注
%K 机器学习
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=5D9F99E1E6A71D6A873E3BCB5D4BDD2F&yid=67289AFF6305E306&vid=D3E34374A0D77D7F&iid=CA4FD0336C81A37A&sid=7E8E8B150580E4AB&eid=C753EB8AC8F551B9&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=7