Japanese Sentence Dataset for Lip- reading

Tatsuya Shirakata, T. Saitoh
{"title":"Japanese Sentence Dataset for Lip- reading","authors":"Tatsuya Shirakata, T. Saitoh","doi":"10.23919/MVA51890.2021.9511353","DOIUrl":null,"url":null,"abstract":"This research is about lip-reading for Japanese sentences. Research on English sentences is actively pursued due to the extensive datasets. However, a sufficient dataset for Japanese sentences has not been released. Therefore, this paper builds a Japanese sentence dataset. A Transformer model is used for the recognition task. Three recognition target levels: phoneme, mora, and vowel, are set, and recognition experiments show that they can be recognized.","PeriodicalId":312481,"journal":{"name":"2021 17th International Conference on Machine Vision and Applications (MVA)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 17th International Conference on Machine Vision and Applications (MVA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/MVA51890.2021.9511353","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

This research is about lip-reading for Japanese sentences. Research on English sentences is actively pursued due to the extensive datasets. However, a sufficient dataset for Japanese sentences has not been released. Therefore, this paper builds a Japanese sentence dataset. A Transformer model is used for the recognition task. Three recognition target levels: phoneme, mora, and vowel, are set, and recognition experiments show that they can be recognized.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
唇读日语句子数据集
本研究是关于日语句子的唇读。由于数据集广泛,对英语句子的研究正在积极进行。然而,一个足够的日语句子数据集还没有发布。因此,本文构建了一个日语句子数据集。Transformer模型用于识别任务。设置了音素、母素和元音三个识别目标层次,并通过识别实验验证了识别目标的有效性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Output augmentation works well without any domain knowledge On the Influence of Viewpoint Change for Metric Learning Shape from shading and polarization constrained by approximate shape Crack Segmentation for Low-Resolution Images using Joint Learning with Super- Resolution Estimating Contribution of Training Datasets using Shapley Values in Data-scale for Visual Recognition
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1