高度屈折的斯洛文尼亚语的两级词汇重音分配模型

T. Sef
{"title":"高度屈折的斯洛文尼亚语的两级词汇重音分配模型","authors":"T. Sef","doi":"10.1109/ICITA.2005.48","DOIUrl":null,"url":null,"abstract":"The paper presents a two level lexical stress assignment model for out of vocabulary Slovenian words used in our text-to-speech system. First, each vowel is determined, whether it is stressed or unstressed, and a type of lexical stress is assigned for every stressed vowel. Then, some corrections are made on the word level, according the number of stressed vowels and the length of the word. We applied a machine-learning technique (decision trees or boosted decision trees). The accuracy achieved by decision trees significantly outperforms all previous results. However, the sizes of the trees indicate that the accentuation in the Slovenian language is a very complex problem and a simple solution in the form of relatively simple rules is not possible.","PeriodicalId":371528,"journal":{"name":"Third International Conference on Information Technology and Applications (ICITA'05)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A two level lexical stress assignment model for highly inflected Slovenian language\",\"authors\":\"T. Sef\",\"doi\":\"10.1109/ICITA.2005.48\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a two level lexical stress assignment model for out of vocabulary Slovenian words used in our text-to-speech system. First, each vowel is determined, whether it is stressed or unstressed, and a type of lexical stress is assigned for every stressed vowel. Then, some corrections are made on the word level, according the number of stressed vowels and the length of the word. We applied a machine-learning technique (decision trees or boosted decision trees). The accuracy achieved by decision trees significantly outperforms all previous results. However, the sizes of the trees indicate that the accentuation in the Slovenian language is a very complex problem and a simple solution in the form of relatively simple rules is not possible.\",\"PeriodicalId\":371528,\"journal\":{\"name\":\"Third International Conference on Information Technology and Applications (ICITA'05)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Third International Conference on Information Technology and Applications (ICITA'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICITA.2005.48\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third International Conference on Information Technology and Applications (ICITA'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITA.2005.48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本文提出了一种两级词汇重音分配模型,用于文本转语音系统中的斯洛文尼亚语词汇。首先,确定每个元音,无论它是重读还是非重读,并且为每个重读元音指定一种词汇重读。然后,根据重读元音的数量和单词的长度,在单词层面上进行一些纠正。我们应用了机器学习技术(决策树或增强决策树)。决策树获得的准确性显著优于所有先前的结果。然而,这些树的大小表明,斯洛文尼亚语中的重音是一个非常复杂的问题,用相对简单的规则来简单解决是不可能的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A two level lexical stress assignment model for highly inflected Slovenian language
The paper presents a two level lexical stress assignment model for out of vocabulary Slovenian words used in our text-to-speech system. First, each vowel is determined, whether it is stressed or unstressed, and a type of lexical stress is assigned for every stressed vowel. Then, some corrections are made on the word level, according the number of stressed vowels and the length of the word. We applied a machine-learning technique (decision trees or boosted decision trees). The accuracy achieved by decision trees significantly outperforms all previous results. However, the sizes of the trees indicate that the accentuation in the Slovenian language is a very complex problem and a simple solution in the form of relatively simple rules is not possible.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信