Syllabic Markov models of Arabic HMMs of spoken Arabic using CV units

M. Ingleby, Fatmah A. Baothman
{"title":"Syllabic Markov models of Arabic HMMs of spoken Arabic using CV units","authors":"M. Ingleby, Fatmah A. Baothman","doi":"10.1109/CIST.2014.7016628","DOIUrl":null,"url":null,"abstract":"We survey evidence - orthographic distributional phonological and psycholinguistic - in favor of a model of Arabic speech sounds based on the CV unit and extensive use of the silent sukuun vowel. We then construct a small-vocabulary multi-speaker CV HMM similar to the phonemic HMMs based on tied triphones that are widely used in speech recognizers for English and other European languages. Using experimental measures of recognition accuracy and trainability, we demonstrate that the CV type of model outperforms a standard tied triphone recognizer for Arabic speech, using Cohen's kappa ration for statistical comparison. Finally we argue that models based on CV units may also lead to better stemmers, spell-checkers and other natural language processing tools for Arabic.","PeriodicalId":106483,"journal":{"name":"2014 Third IEEE International Colloquium in Information Science and Technology (CIST)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Third IEEE International Colloquium in Information Science and Technology (CIST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIST.2014.7016628","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

We survey evidence - orthographic distributional phonological and psycholinguistic - in favor of a model of Arabic speech sounds based on the CV unit and extensive use of the silent sukuun vowel. We then construct a small-vocabulary multi-speaker CV HMM similar to the phonemic HMMs based on tied triphones that are widely used in speech recognizers for English and other European languages. Using experimental measures of recognition accuracy and trainability, we demonstrate that the CV type of model outperforms a standard tied triphone recognizer for Arabic speech, using Cohen's kappa ration for statistical comparison. Finally we argue that models based on CV units may also lead to better stemmers, spell-checkers and other natural language processing tools for Arabic.
使用CV单位的阿拉伯语口语hmm的音节马尔可夫模型
我们调查证据-正字法分布音韵学和心理语言学-支持基于CV单位和广泛使用沉默sukuun元音的阿拉伯语音模型。然后,我们构建了一个类似于音素HMM的小词汇多扬声器CV HMM,该HMM基于捆绑三音,广泛用于英语和其他欧洲语言的语音识别。使用识别精度和可训练性的实验测量,我们证明了CV类型的模型优于标准的阿拉伯语音绑定三音识别器,使用Cohen的kappa比率进行统计比较。最后,我们认为基于CV单位的模型也可以为阿拉伯语提供更好的词干器、拼写检查器和其他自然语言处理工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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